Single event effects (SEEs) are individual events which occur when a single incident ionizing particle deposits enough energy to cause an effect in a device. SEEs are generally caused by two space radiation sources: high energy protons, and cosmic rays. Single event phenomenon can be classified into four: (i) single event upset (SEU), (ii) single event latch-up (SEL), (iii) single event burnout (SEB) and (iv) single event gate rupture (SEGR). SEU is a change of state caused by ions or electromagnetic radiation striking a sensitive node in a micro-electronic device, such as in a microprocessor, semiconductor memory, or power transistors. The state change is a result of the free charge created by ionization in or close to an important node of a logic element (e.g., memory bit). The error in device output or operation

#### **Figure 4.**

*(a) Satellite's charge control mechanism, and (b) differential charging in satellites due to self-shadowing (source: Ref. [12]).*

**79**

**Figure 5.**

BJTs, and CMOS.

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

SEFI halts normal operations, and requires a power reset to recover [1].

caused as a result of the strike is called a soft error. The mechanisms for heavy ion and proton SEU in devices (e.g., dynamic random access memories (DRAM)), and galactic cosmic ray energy deposition in devices are depicted in **Figure 5**. SEU can cause a reset or re-writing in normal device such as in analogue, digital, or optical components, and may also have effects in surrounding interface circuitry. A severe SEU is the single-event functional interrupt (SEFI) in which an SEU in the device's control circuitry places the device into a test mode, halt, or undefined state. The

SEL is used in integrated circuits (ICs) to describe a particular type of short circuit which can occur in an improperly designed circuit. It is the generation of a low-impedance path between the power supply rails of a MOSFET circuit that can trigger a parasitic structure which disrupts proper functioning of the part and possibly even leading to its destruction due to over-current. SELs are hard errors, and can cause permanent damage. It can results in a high operating current, above device specifications, drag down the bus voltage, or damage the power supply. Latch-up can be caused by protons in very sensitive devices [22]. An SEL is corrected or cleared by a power off–on reset or power strobing of the device. SEL is strongly temperature dependent. If power is not removed quickly, catastrophic failure may occur due to excessive heating or metallization or bond wire failure [23]. SEB is a condition caused by high current state in a power transistor. It is a highly localized phenomenon, and includes burnout of the drain-source in power MOSFETs and BJTs, gate rupture, frozen bits, and noise in charged-coupled devices (CCDs). SEGR is the formation of a conducting path or localized dielectric breakdown in the gate oxide resulting in a destructive burnout. It occurs at MOSFETs,

*(a) Mechanisms for heavy ion and proton SEU, (b) schematic showing how GCR deposit energy in an electronic device [12], and (c) upset mechanism for dynamic random-access memories (DRAMs) (from Ref. [21]).*

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

#### *The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

caused as a result of the strike is called a soft error. The mechanisms for heavy ion and proton SEU in devices (e.g., dynamic random access memories (DRAM)), and galactic cosmic ray energy deposition in devices are depicted in **Figure 5**. SEU can cause a reset or re-writing in normal device such as in analogue, digital, or optical components, and may also have effects in surrounding interface circuitry. A severe SEU is the single-event functional interrupt (SEFI) in which an SEU in the device's control circuitry places the device into a test mode, halt, or undefined state. The SEFI halts normal operations, and requires a power reset to recover [1].

SEL is used in integrated circuits (ICs) to describe a particular type of short circuit which can occur in an improperly designed circuit. It is the generation of a low-impedance path between the power supply rails of a MOSFET circuit that can trigger a parasitic structure which disrupts proper functioning of the part and possibly even leading to its destruction due to over-current. SELs are hard errors, and can cause permanent damage. It can results in a high operating current, above device specifications, drag down the bus voltage, or damage the power supply. Latch-up can be caused by protons in very sensitive devices [22]. An SEL is corrected or cleared by a power off–on reset or power strobing of the device. SEL is strongly temperature dependent. If power is not removed quickly, catastrophic failure may occur due to excessive heating or metallization or bond wire failure [23].

SEB is a condition caused by high current state in a power transistor. It is a highly localized phenomenon, and includes burnout of the drain-source in power MOSFETs and BJTs, gate rupture, frozen bits, and noise in charged-coupled devices (CCDs). SEGR is the formation of a conducting path or localized dielectric breakdown in the gate oxide resulting in a destructive burnout. It occurs at MOSFETs, BJTs, and CMOS.

#### **Figure 5.**

*(a) Mechanisms for heavy ion and proton SEU, (b) schematic showing how GCR deposit energy in an electronic device [12], and (c) upset mechanism for dynamic random-access memories (DRAMs) (from Ref. [21]).*

*Satellites Missions and Technologies for Geosciences*

**3.2 Single event effects (SEEs)**

effects, electrostatic discharges appear to be the most dangerous of all. Electrostatic discharges can cause structural damage, degradation of spacecraft components and operational anomalies due to damages to electronics. SC can be categorised into two: Surface charging which include differential charging, and internal dielectric charging. Surface charging is caused by low energy plasma (<100 keV) and photoelectric currents. Surface charging can either be absolute or differential. Absolute charging occurs when the satellite potential relative to the ambient plasma is charged uniformly, while differential charging occurs when parts of the spacecraft are charged to different potential relative to one another. Differential charging can also be caused by satellite self-shadowing. The charge control mechanism, and differential charging in spacecrafts are depicted in **Figure 4**. Differential charging of spacecraft surfaces is more detrimental than the absolute charging (relative to ambient plasma). The former can have a discharge effects that can disrupt satellite operations such as physical materials damage and electromagnetic interference (EMI) generation, and resultant transient pulses. Discharge consequences also include noise in data and wiring, sputtering and attraction of chemically active species [18]. Differential charging has been reported after geomagnetic sub-storms,

which result in the injection of keV electrons into the magnetosphere.

Internal charging is caused by high-energy electrons (>100 keV), which penetrate into the spacecraft equipment where they deposit charge inside insulating materials [8]. Internal discharge is more damaging since it occurs within dielectric materials and well-insulated conductors, which are in close proximity to sensitive electronic circuitry [19]. Based on data from the Combined Release and Radiation Effects Satellite (CRRES) obtained at GEO, most environmentally induced spacecraft anomalies result from deep dielectric charging and the resulting discharge pulses and not from surface insulator charging or single-event upsets [20].

Single event effects (SEEs) are individual events which occur when a single incident ionizing particle deposits enough energy to cause an effect in a device. SEEs are generally caused by two space radiation sources: high energy protons, and cosmic rays. Single event phenomenon can be classified into four: (i) single event upset (SEU), (ii) single event latch-up (SEL), (iii) single event burnout (SEB) and (iv) single event gate rupture (SEGR). SEU is a change of state caused by ions or electromagnetic radiation striking a sensitive node in a micro-electronic device, such as in a microprocessor, semiconductor memory, or power transistors. The state change is a result of the free charge created by ionization in or close to an important node of a logic element (e.g., memory bit). The error in device output or operation

*(a) Satellite's charge control mechanism, and (b) differential charging in satellites due to self-shadowing*

**78**

**Figure 4.**

*(source: Ref. [12]).*

Solar flare particle events pose the most extreme SEU producing environment, especially for spacecraft in interplanetary space [24]. Experiments aboard CRRES showed a significant increase during a solar flare [25]. Based on CRRES's data, most SEUs come from high energy protons through nuclear interactions and not through direct deposition from either protons or cosmic rays [20]. For LEO satellites, trapped protons, especially in the SAA, are the greatest SEE threat.

#### **3.3 Total ionizing dose (TID)**

Total ionizing dose (TID) refers to the amount of energy that ionization processes create and deposit in materials such as semiconductor or insulator when energized particles pass through it. TID can result in device failure or biological damage to astronauts. Radiation-induced trapped charges can build up in the gate oxide of a MOSFET and cause a shift in the threshold voltage. Such device cannot be turned off even at zero volts applied, if the shift is large enough. Under this condition the device is said to have failed by going into depletion mode [26]. TID is mostly due to electrons and protons, mainly from solar energetic particle event and passage through the SAA. In low Earth orbit, the main dose source is from electrons and inner belt protons, while the primary source is outer belt electron and solar protons in geostationary orbit. The first recorded satellite failure resulting from total dose was the Telstar. The satellite was launched a day after the Starfish nuclear test on 9 July 1962. The nuclear weapon of about 1.4 Megaton was detonated at an altitude of about 400 km above Johnston Island in the Pacific Ocean. The explosion produced beta particles (electrons) that were injected into the Earth's magnetic field, forming an artificial radiation belt. This artificial electron belt lasted until the early 1970s. Consequently, Telstar experienced a total dose 100 times that expected before its total failure. Up to seven satellites were destroyed by the Starfish nuclear test within 7 months mainly from solar cell damage [12].

#### **3.4 Displacement damage (DD)**

When energetic particles are incident on a solid material, they lose their energy to ionizing and non-ionizing processes as they travel through the material. The consequence of the energy loss is in the production of electron–hole pairs and atoms displacement or displacement damage. Vacancies (i.e., absence of an atom from its normal lattice position) and interstitials (i.e., movement of displaced atom into a non-lattice position) are the primary lattice defects that are initially created. The combination of a vacancy and an adjacent interstitial is known as a Frenkel or close pair. Two adjacent vacancies can form a defect known as divacancy. Also, larger local groupings of vacancies may occur in irradiated silicon. A defect resulting from vacancy and interstitials being adjacent to impurity atoms is known as defect-impurity complexes. Once formed by incident radiation, the defects will reorder to form more stable configuration. The extent to which defects alter the properties of bulk semiconductor material and devices depends on nature of the particular defects and the time following the creation of defect at a given temperature.

The effectiveness of radiation-induced displacement damage depends on factors such as bombardment condition, particle type and energy, irradiation and measurement temperature, time after irradiation, thermal history after irradiation, injection level, material type, impurity type and concentration [27]. Displacement damage causes degradation of materials and device properties. **Figure 6** depicts the collision between an incoming particle and a lattice atom, causing the displacement

**81**

given by:

*S* = −

constant (= 8.99 × 109

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

of the atom from its original lattice position. Displacement damage can also degrade minority carrier lifetime, and a typical effect would be degradation of gain and

The review presented here include portion of the work [1], part of which was published in [2]. We analyzed particles, electrons and protons flux of various energies from NOAA database for 3 months (April–June 2010). The mass stopping power, range and possible deposited dose of protons were calculated, and applied to the scenario of possible interaction of the particles with satellite surface and its

Stopping power is the average energy loss of a particle per unit length (measured in MeV/cm) when passing through the material. Charged particles are known to ionize the atom or molecule which they encounter when passing through matter, and they lose energy in the process. The stopping power depends on the type and energy of the particle and on the properties of the material it passes. Although numerical values and units are identical for both quantities, the Stopping power refers to the property of the material while energy loss per unit path length describes what happens to the particle. The density of ionization along the particles path is proportional to the stopping power of the material because the production of an ion pairs requires a fixed amount of energy [28]. The Bethe-Bloch formula for stopping power derived from relativistic quantum mechanics is

**4. The stopping power, range of particles and deposited dose in**

*Displacement of atom from its original lattice position by incoming particle through collision [12].*

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

leakage current in bipolar transistors [12].

electrical, electronic and electrochemical components.

\_ *dE dx* = 4*π z*2

N m2

 C−2 ).

 *k*0 2 *e* \_

*m v*2

4

[ln

2*m v* \_ 2 *I* − *ln* (1 −

where *z* is the atomic number of the heavy particle, *e* is magnitude of the electron charge, *m* is the electron rest mass, *c* is the speed of light, *I* is the mean excitation energy of the medium, *v* is the velocity of the particle and *k*0 is the Boltzmann

*v*2 \_ *c*2 ) − *v*2 \_ *c*2 ]

**spacecraft materials**

**Figure 6.**

**4.1 Stopping power**

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

**Figure 6.**

*Satellites Missions and Technologies for Geosciences*

**3.3 Total ionizing dose (TID)**

Solar flare particle events pose the most extreme SEU producing environment, especially for spacecraft in interplanetary space [24]. Experiments aboard CRRES showed a significant increase during a solar flare [25]. Based on CRRES's data, most SEUs come from high energy protons through nuclear interactions and not through direct deposition from either protons or cosmic rays [20]. For LEO satellites,

Total ionizing dose (TID) refers to the amount of energy that ionization processes create and deposit in materials such as semiconductor or insulator when energized particles pass through it. TID can result in device failure or biological damage to astronauts. Radiation-induced trapped charges can build up in the gate oxide of a MOSFET and cause a shift in the threshold voltage. Such device cannot be turned off even at zero volts applied, if the shift is large enough. Under this condition the device is said to have failed by going into depletion mode [26]. TID is mostly due to electrons and protons, mainly from solar energetic particle event and passage through the SAA. In low Earth orbit, the main dose source is from electrons and inner belt protons, while the primary source is outer belt electron and solar protons in geostationary orbit. The first recorded satellite failure resulting from total dose was the Telstar. The satellite was launched a day after the Starfish nuclear test on 9 July 1962. The nuclear weapon of about 1.4 Megaton was detonated at an altitude of about 400 km above Johnston Island in the Pacific Ocean. The explosion produced beta particles (electrons) that were injected into the Earth's magnetic field, forming an artificial radiation belt. This artificial electron belt lasted until the early 1970s. Consequently, Telstar experienced a total dose 100 times that expected before its total failure. Up to seven satellites were destroyed by the Starfish nuclear

When energetic particles are incident on a solid material, they lose their energy to ionizing and non-ionizing processes as they travel through the material. The consequence of the energy loss is in the production of electron–hole pairs and atoms displacement or displacement damage. Vacancies (i.e., absence of an atom from its normal lattice position) and interstitials (i.e., movement of displaced atom into a non-lattice position) are the primary lattice defects that are initially created. The combination of a vacancy and an adjacent interstitial is known as a Frenkel or close pair. Two adjacent vacancies can form a defect known as divacancy. Also, larger local groupings of vacancies may occur in irradiated silicon. A defect resulting from vacancy and interstitials being adjacent to impurity atoms is known as defect-impurity complexes. Once formed by incident radiation, the defects will reorder to form more stable configuration. The extent to which defects alter the properties of bulk semiconductor material and devices depends on nature of the particular defects and the time following the creation of defect at a given

The effectiveness of radiation-induced displacement damage depends on factors such as bombardment condition, particle type and energy, irradiation and measurement temperature, time after irradiation, thermal history after irradiation, injection level, material type, impurity type and concentration [27]. Displacement damage causes degradation of materials and device properties. **Figure 6** depicts the collision between an incoming particle and a lattice atom, causing the displacement

trapped protons, especially in the SAA, are the greatest SEE threat.

test within 7 months mainly from solar cell damage [12].

**3.4 Displacement damage (DD)**

**80**

temperature.

*Displacement of atom from its original lattice position by incoming particle through collision [12].*

of the atom from its original lattice position. Displacement damage can also degrade minority carrier lifetime, and a typical effect would be degradation of gain and leakage current in bipolar transistors [12].

#### **4. The stopping power, range of particles and deposited dose in spacecraft materials**

The review presented here include portion of the work [1], part of which was published in [2]. We analyzed particles, electrons and protons flux of various energies from NOAA database for 3 months (April–June 2010). The mass stopping power, range and possible deposited dose of protons were calculated, and applied to the scenario of possible interaction of the particles with satellite surface and its electrical, electronic and electrochemical components.

#### **4.1 Stopping power**

Stopping power is the average energy loss of a particle per unit length (measured in MeV/cm) when passing through the material. Charged particles are known to ionize the atom or molecule which they encounter when passing through matter, and they lose energy in the process. The stopping power depends on the type and energy of the particle and on the properties of the material it passes. Although numerical values and units are identical for both quantities, the Stopping power refers to the property of the material while energy loss per unit path length describes what happens to the particle. The density of ionization along the particles path is proportional to the stopping power of the material because the production of an ion pairs requires a fixed amount of energy [28]. The Bethe-Bloch formula for stopping power derived from relativistic quantum mechanics is given by: *e* \_

en by:
$$S = -\frac{dE}{dx} = \frac{4\pi x^2 k\_0^2 e^4}{m\nu^2} \left[ \ln \frac{2m\nu^2}{I} - \ln \left( \mathbf{1} - \frac{\nu^2}{c^2} \right) - \frac{\nu^2}{c^2} \right]$$

where *z* is the atomic number of the heavy particle, *e* is magnitude of the electron charge, *m* is the electron rest mass, *c* is the speed of light, *I* is the mean excitation energy of the medium, *v* is the velocity of the particle and *k*0 is the Boltzmann constant (= 8.99 × 109 N m2 C−2 ).

The mass stopping power of the material is obtained by dividing the stopping power by the density (*ρ*) of the material. It is a useful quantity because it expresses the rate of energy loss of the charged particle per g/cm2 of the medium traversed [28].

$$-\frac{1}{\tau}$$

$$S = -\frac{dE}{\rho dx}$$

#### **4.2 The range of particle**

The range *R* of a particle (e.g., proton) of initial kinetic energy *Ek* and mass *m* is the mean distance it travels before coming to a stop. *R* depends on the particle type, initial energy and the material through which it traverses. A theoretical approach to the determination of charged particle range utilizes stopping power expression. The range of a proton computed by numerical integration of the stopping power using the continuous slowing down approximation (CSDA) is given by:

$$\begin{aligned} \text{If } \mathbf{u} \text{ and } \mathbf{v} \text{ are } \dots \text{ then } \\ \mathbf{R} = \int\_{E\_{\text{min}}}^{E\_{\text{max}}} \left( -\frac{dE}{\rho dx} \right)^{-1} dE + R(E\_{\text{min}}) \end{aligned}$$

where *R* (*Emin*) is the measured range at minimum energy *Emin* which is added to the integral equation and treated as a constant for a particle and material. For the calculations of ranges for proton *Emin* is taken to be as 1 MeV as much data is available at 1 Mev. *R* (*Emax*) is the measured range at maximum energy *Emax.*

In previous work we used the empirical relations suggested by [28] to calculate the mass stopping power of particles in spacecraft materials [1, 2]. However, we anticipate limitations in the equations because they were originally formulated for low energy particles. Values obtained using Bethe's equations are higher and assumed more accurate at higher particle energies.

#### **4.3 Dose deposition and absorption**

The total ionizing dose (TID), explained in Section 3.3, can be measured in terms of the absorbed dose; which is a measure of the energy absorbed by matter. Absorbed dose is quantified using either a unit called the rad (radiation absorbed dose) or the SI unit which is the gray (Gy). 1 Gy = 100 rads = 1 J/kg. The total accumulated dose on a satellite depends on orbit altitude, orientation, and time spent in orbit. To compute TID we need to know the integrated particle energy spectrum, ø(*E*) or the fluence as a function of particle energy. The dose is a function of the particle flux. It becomes important as the spacecraft spends more time in the space radiation environment. The stopping power is used to determine dose from charged particle by the following relationship:

 $\omega\_1$  הוא  $\omega\_2$  הוא הוא הוא הוא  $\omega\_3$
$$D = \mathcal{Q} \frac{dE}{\rho dx}$$

where ∅ is the particle fluence (i.e., the number of particles striking the material over a specified time interval).

Satellite and space probes typically encounter TID between 10 krad (100 Gy) and 100 krad(Si) (1000 Gy(Si)). The time taken, *t* (in years) for a satellite's component to fail due to total ionizing dose can be obtained by dividing the maximum absorbed dose or TID threshold by the total absorbed dose per year, given as: *t* (*in yrs*) = \_

$$t \text{ (} in \text{ } jrrs\text{) } = \frac{TID\_{\text{rhredolold}}}{Dose/yr}$$

**83**

**Figure 7.**

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

model satellite's component within 3 years and 100 krad within 29 years.

The electrons impinging on spacecraft surface in the space environment are faster than their ion counterpart because of their very small mass (when compared to that of ions). As a result the ambient electron flux is usually more than the ambient ion flux, leading to high level negative charging of the spacecraft. The regions of concern (in space) for internal charging of spacecrafts is illustrated in [29] and shown in **Figure 7**. Spacecraft charging can be mitigated by the methods of electron emission and ion reception [30]. Electron emission is the method in which a device pulls (or draws) electrons from the spacecraft ground and ejects them into space, while the ion reception is the method in which positive ions arrive at a spacecraft that is negatively charged to neutralize the negative charges. The former method is effective for reducing the negative charge of the spacecraft ground but not effective for dielectric surfaces. As a demerit, the process can lead to differential charging between the dielectric and the conducting ground. The later method is effective for mitigating negatively charged surface (whether dielectric or conductor), and reducing differential charging. However, it has the disadvantage of electroplating the entire spacecraft with extended use. Because each method has advantage (or disadvantage) over the other, the use of a combination of both types has been recommended. Other mitigation methods include plasma emission, partially conducting paint, polar molecule emission, mirror reflection and violet

**5. Mitigating the impact of space radiation environment**

*Regions of concern for internal charging of spacecrafts in space (source: Ref. [29]).*

made of aluminum alloy and 20 mm thickness (without impact mitigation such as protective coating on the satellite), in which the electrical, electronic and electrochemical components (mainly of silicon (Si) and germanium (Ge) materials) are housed [1, 2]. Our calculations were based on particles with E ≥ 78 MeV. When particles of this energy range bombard and penetrate the satellite, parts of their energies are lost due to the stopping power of the alloy but the reminder constitute significant dose to the components. With continuous exposure, the dose continues to build over time until the threshold is exceeded leading to completed failure of the affected satellite. Our calculations showed that a dose of 10 krad can build up on the

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

**5.1 Spacecraft charging**

irradiation [31].

We performed theoretical calculations to predict the mean time to failure of a model satellite due to TID. The assumption is that the model satellite's body is

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

made of aluminum alloy and 20 mm thickness (without impact mitigation such as protective coating on the satellite), in which the electrical, electronic and electrochemical components (mainly of silicon (Si) and germanium (Ge) materials) are housed [1, 2]. Our calculations were based on particles with E ≥ 78 MeV. When particles of this energy range bombard and penetrate the satellite, parts of their energies are lost due to the stopping power of the alloy but the reminder constitute significant dose to the components. With continuous exposure, the dose continues to build over time until the threshold is exceeded leading to completed failure of the affected satellite. Our calculations showed that a dose of 10 krad can build up on the model satellite's component within 3 years and 100 krad within 29 years.

#### **5. Mitigating the impact of space radiation environment**

#### **5.1 Spacecraft charging**

*Satellites Missions and Technologies for Geosciences*

**4.2 The range of particle**

*R* = ∫

**4.3 Dose deposition and absorption**

particle by the following relationship:

over a specified time interval).

*D* = ∅

*t* (*in yrs*) = \_

the rate of energy loss of the charged particle per g/cm2

the continuous slowing down approximation (CSDA) is given by:

*Emin Emax* (− \_ *dE dx*) −1

assumed more accurate at higher particle energies.

able at 1 Mev. *R* (*Emax*) is the measured range at maximum energy *Emax.*

The mass stopping power of the material is obtained by dividing the stopping power by the density (*ρ*) of the material. It is a useful quantity because it expresses

> *S* = − \_ *dE dx*

The range *R* of a particle (e.g., proton) of initial kinetic energy *Ek* and mass *m* is the mean distance it travels before coming to a stop. *R* depends on the particle type, initial energy and the material through which it traverses. A theoretical approach to the determination of charged particle range utilizes stopping power expression. The range of a proton computed by numerical integration of the stopping power using

where *R* (*Emin*) is the measured range at minimum energy *Emin* which is added to the integral equation and treated as a constant for a particle and material. For the calculations of ranges for proton *Emin* is taken to be as 1 MeV as much data is avail-

In previous work we used the empirical relations suggested by [28] to calculate the mass stopping power of particles in spacecraft materials [1, 2]. However, we anticipate limitations in the equations because they were originally formulated for low energy particles. Values obtained using Bethe's equations are higher and

The total ionizing dose (TID), explained in Section 3.3, can be measured in terms of the absorbed dose; which is a measure of the energy absorbed by matter. Absorbed dose is quantified using either a unit called the rad (radiation absorbed dose) or the SI unit which is the gray (Gy). 1 Gy = 100 rads = 1 J/kg. The total accumulated dose on a satellite depends on orbit altitude, orientation, and time spent in orbit. To compute TID we need to know the integrated particle energy spectrum, ø(*E*) or the fluence as a function of particle energy. The dose is a function of the particle flux. It becomes important as the spacecraft spends more time in the space radiation environment. The stopping power is used to determine dose from charged

\_ *dE dx* where ∅ is the particle fluence (i.e., the number of particles striking the material

> *TIDthreshold Dose*/*yr*

Satellite and space probes typically encounter TID between 10 krad (100 Gy) and 100 krad(Si) (1000 Gy(Si)). The time taken, *t* (in years) for a satellite's component to fail due to total ionizing dose can be obtained by dividing the maximum absorbed dose or TID threshold by the total absorbed dose per year, given as:

We performed theoretical calculations to predict the mean time to failure of a model satellite due to TID. The assumption is that the model satellite's body is

*dE* + *R*(*Emin*)

of the medium traversed [28].

**82**

The electrons impinging on spacecraft surface in the space environment are faster than their ion counterpart because of their very small mass (when compared to that of ions). As a result the ambient electron flux is usually more than the ambient ion flux, leading to high level negative charging of the spacecraft. The regions of concern (in space) for internal charging of spacecrafts is illustrated in [29] and shown in **Figure 7**. Spacecraft charging can be mitigated by the methods of electron emission and ion reception [30]. Electron emission is the method in which a device pulls (or draws) electrons from the spacecraft ground and ejects them into space, while the ion reception is the method in which positive ions arrive at a spacecraft that is negatively charged to neutralize the negative charges. The former method is effective for reducing the negative charge of the spacecraft ground but not effective for dielectric surfaces. As a demerit, the process can lead to differential charging between the dielectric and the conducting ground. The later method is effective for mitigating negatively charged surface (whether dielectric or conductor), and reducing differential charging. However, it has the disadvantage of electroplating the entire spacecraft with extended use. Because each method has advantage (or disadvantage) over the other, the use of a combination of both types has been recommended. Other mitigation methods include plasma emission, partially conducting paint, polar molecule emission, mirror reflection and violet irradiation [31].

**Figure 7.** *Regions of concern for internal charging of spacecrafts in space (source: Ref. [29]).*

#### **5.2 Single event effects**

For memories and data related devices, some of the error mitigation approach or methods include Parity check, cyclic-redundancy check (CRC) coding, Hamming code, Reed-Solomon (R-S) coding, convolutional encoding and overlying protocol (see: Ref. [32] and references therein). Parity is a single bit added to the end of a data structure, such that it states whether an odd or even number of 'ones' was in the structure. The parity method counts the number of logic-one states or 'ones' that are occurring in a data path. The CRC coding method detects if any errors occurred in a given data structure based on performing modulo-two arithmetic operations on a given stream of data, and interpreting the results as a polynomial. The hamming code method detects the position of a single error and the existence of more than one error in a data structure. The R-S code can detect and correct multiple and consecutive errors in a data structure. The convolutional encoding can also detect and correct multiple bit errors. However, it is distinguishable from block coding (e.g., R-S code) by interleave of the overhead or check bits into the actual stream of data instead of being grouped into separate words at the end of the data structure. Errors in the control-related devices can also be mitigated using some of the above mentioned methods. A more effective mitigation approach for controlrelated devices with complex difficulties (e.g., large scale integration circuitry or microprocessors) is the software-based mitigation, which includes tasks or subroutines dubbed health and safety (H&S). The H&S tasks can perform memory scrubbing that utilizes parity or other method on either external memory devices or registers that are internal to the microprocessor. In the software mitigation methods, the internal microprocessor timers can also be used to operate a watchdog timer or for passing H&S messages between spacecraft systems (see: Ref. [32] for more detail).

#### **5.3 Total ionizing dose**

TID on satellites system can be mitigated by methods such as shielding, derating and conservative circuit design [33]. Shielding is the processes of protecting spacecraft (and the occupants) from ionizing radiation using a configuration of appropriate massive materials. Derating refers to techniques usually employed in electrical power and electronic devices in which devices are operated at maximum power dissipation that is less than their rated value, with consideration of the case or body temperature, ambient temperature and the type of cooling mechanism used. This method can increase the safety margin between part design limits and applied stresses, consequently enhancing protection of the part [34]. Hardening of critical components in satellites at design level is also a viable method. This has, however, been the practice of satellite manufacturers. These methods can also be used to mitigate *Displacement damage* because DD is similar to TID as the effect is also cumulative [33].

Other important mitigation approach includes the development of appropriate environmental model that can mimic the perturbed scenarios that are expected under extreme space environmental condition. A well-accomplished or more sophisticated model should account for the individual effects of various solar forcing mechanisms, which cause fluctuations in neutral and ionized density [35]. One other very important mitigation approach to consider is the development of extensive warning system for solar energetic events. Although solar activity can be predicted days in advance but ascertaining their level of impact on the satellite and the Earth environment is quite challenging. Therefore, effective monitoring of solar activity is essential in order to be able to predict atmospheric or ionospheric

**85**

shown in **Figure 8**.

**Figure 8.**

**6. Conclusion**

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

responses to solar events and their consequence on satellite in orbit. In all, orbit consideration (and satellite's trajectory) is also important. Satellites in medium Earth orbit (MEO) and geostationary orbit (GEO) are subject to impacts of outer Van Allen radiation belt. LEO satellites encounter the most intense particle fluxes in the SAA [36], which is considered to be the main region where spacecrafts receive the largest fraction of the radiation exposure during spaceflight missions. The schematic diagram of Earth's radiation belts and their space weather concerns is

*Schematic diagram of Earth's radiation belts and their space weather concerns (from Ref. [36]).*

The space radiation environment driven by solar activity (and galactic cosmic rays) poses potent and unequivocal treat to satellites in near-Earth space. Understanding atmospheric and ionospheric dynamic responses to solar-driven particles and radiation, and their space weather implications are critical and of practical importance to satellites design and operation. The specific effects of radiation environment on as satellite depends on the source, type and energy of incident particle, as well as the satellite's orbit and/or position at the time of solar energetic events. Radiation mitigation measures can increase the safety margin between part design limits and the applied stresses resulting from particles impact, consequently enhancing protection of the part. However, it is important that the solar maximum phase be given more consideration in all mitigation effort because the rate of impact is higher during this interval. Severe solar storms can occur during the solar maximum that can produce huge short-lived increase in radiation levels, as well as high levels of SEEs that current mitigation measures might not be able to bear [37]. Also as dependence on satellites services increase, the economic and societal risk associated with space weather also increases, and likely impact can be unprecedented. In view of this, a contingency plans that include the possibility of switching to or benefitting from other independent satellite services have been recommended [8]. The upcoming multi-constellation GNSS receivers can play a significant role in this regard, such that the individual GNSS receivers will be inherently robust to a satellite service denial. Space weather-induced enhancement of atmospheric drag on satellites and consequent accelerated orbit decay is also a major perturbing force to reckon with, for satellites in low Earth orbit [35, 38–42]. A concise review of the impact and mitigation of this phenomenon will be published in the future. We note

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

**Figure 8.** *Schematic diagram of Earth's radiation belts and their space weather concerns (from Ref. [36]).*

responses to solar events and their consequence on satellite in orbit. In all, orbit consideration (and satellite's trajectory) is also important. Satellites in medium Earth orbit (MEO) and geostationary orbit (GEO) are subject to impacts of outer Van Allen radiation belt. LEO satellites encounter the most intense particle fluxes in the SAA [36], which is considered to be the main region where spacecrafts receive the largest fraction of the radiation exposure during spaceflight missions. The schematic diagram of Earth's radiation belts and their space weather concerns is shown in **Figure 8**.

#### **6. Conclusion**

*Satellites Missions and Technologies for Geosciences*

For memories and data related devices, some of the error mitigation approach or methods include Parity check, cyclic-redundancy check (CRC) coding, Hamming code, Reed-Solomon (R-S) coding, convolutional encoding and overlying protocol (see: Ref. [32] and references therein). Parity is a single bit added to the end of a data structure, such that it states whether an odd or even number of 'ones' was in the structure. The parity method counts the number of logic-one states or 'ones' that are occurring in a data path. The CRC coding method detects if any errors occurred in a given data structure based on performing modulo-two arithmetic operations on a given stream of data, and interpreting the results as a polynomial. The hamming code method detects the position of a single error and the existence of more than one error in a data structure. The R-S code can detect and correct multiple and consecutive errors in a data structure. The convolutional encoding can also detect and correct multiple bit errors. However, it is distinguishable from block coding (e.g., R-S code) by interleave of the overhead or check bits into the actual stream of data instead of being grouped into separate words at the end of the data structure. Errors in the control-related devices can also be mitigated using some of the above mentioned methods. A more effective mitigation approach for controlrelated devices with complex difficulties (e.g., large scale integration circuitry or microprocessors) is the software-based mitigation, which includes tasks or subroutines dubbed health and safety (H&S). The H&S tasks can perform memory scrubbing that utilizes parity or other method on either external memory devices or registers that are internal to the microprocessor. In the software mitigation methods, the internal microprocessor timers can also be used to operate a watchdog timer or for passing H&S messages between spacecraft systems (see: Ref. [32] for

TID on satellites system can be mitigated by methods such as shielding, derating and conservative circuit design [33]. Shielding is the processes of protecting spacecraft (and the occupants) from ionizing radiation using a configuration of appropriate massive materials. Derating refers to techniques usually employed in electrical power and electronic devices in which devices are operated at maximum power dissipation that is less than their rated value, with consideration of the case or body temperature, ambient temperature and the type of cooling mechanism used. This method can increase the safety margin between part design limits and applied stresses, consequently enhancing protection of the part [34]. Hardening of critical components in satellites at design level is also a viable method. This has, however, been the practice of satellite manufacturers. These methods can also be used to mitigate *Displacement damage* because DD is similar to TID as the effect is

Other important mitigation approach includes the development of appropriate environmental model that can mimic the perturbed scenarios that are expected under extreme space environmental condition. A well-accomplished or more sophisticated model should account for the individual effects of various solar forcing mechanisms, which cause fluctuations in neutral and ionized density [35]. One other very important mitigation approach to consider is the development of extensive warning system for solar energetic events. Although solar activity can be predicted days in advance but ascertaining their level of impact on the satellite and the Earth environment is quite challenging. Therefore, effective monitoring of solar activity is essential in order to be able to predict atmospheric or ionospheric

**5.2 Single event effects**

more detail).

**5.3 Total ionizing dose**

also cumulative [33].

**84**

The space radiation environment driven by solar activity (and galactic cosmic rays) poses potent and unequivocal treat to satellites in near-Earth space. Understanding atmospheric and ionospheric dynamic responses to solar-driven particles and radiation, and their space weather implications are critical and of practical importance to satellites design and operation. The specific effects of radiation environment on as satellite depends on the source, type and energy of incident particle, as well as the satellite's orbit and/or position at the time of solar energetic events. Radiation mitigation measures can increase the safety margin between part design limits and the applied stresses resulting from particles impact, consequently enhancing protection of the part. However, it is important that the solar maximum phase be given more consideration in all mitigation effort because the rate of impact is higher during this interval. Severe solar storms can occur during the solar maximum that can produce huge short-lived increase in radiation levels, as well as high levels of SEEs that current mitigation measures might not be able to bear [37]. Also as dependence on satellites services increase, the economic and societal risk associated with space weather also increases, and likely impact can be unprecedented. In view of this, a contingency plans that include the possibility of switching to or benefitting from other independent satellite services have been recommended [8]. The upcoming multi-constellation GNSS receivers can play a significant role in this regard, such that the individual GNSS receivers will be inherently robust to a satellite service denial. Space weather-induced enhancement of atmospheric drag on satellites and consequent accelerated orbit decay is also a major perturbing force to reckon with, for satellites in low Earth orbit [35, 38–42]. A concise review of the impact and mitigation of this phenomenon will be published in the future. We note

that this review (on the space radiation effects on satellites and their mitigation methods) is succinct when compared to the large body of work in the subject area. Therefore, we encourage readers to also consult other well-accomplished texts for specific space radiation effect and the appropriate mitigation approach.

### **Author details**

Victor U.J. Nwankwo1 \*, Nnamdi N. Jibiri2 and Michael T. Kio3

1 Space, Atmospheric Physics and Radio Wave Propagation Laboratory, Department of Physics, Anchor University, Lagos, Nigeria

2 Radiation and Health Physics Laboratory, Department of Physics, University of Ibadan, Ibadan, Nigeria

3 Engineering and Space Systems Department, National Space and Research Development Agency, Abuja, Nigeria

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**87**

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

2010

Resource; 2019

10.17226/24993

Infrastructure. London: Royal Academy

[9] Allen JH, Wilkinson D. Spacecraft charging: Then and now. In: Spacecraft charging technology conference, Albuquerque, NM, 20-24 September

[10] National Weather Service (NWS).

[11] The National Academies of Sciences, Engineering and Medicine. Testing at the speed of light: The State of U.S. In: Electronic Parts Space Radiation Testing Infrastructure. Washington, DC: The National Academic Press; 2018. DOI:

[12] Holbert KE. Space Radiation Environmental Effects. Courses in Electrical Engineering, Arizona State University. 2007. Available from: http:// holbert.faculty.asu.edu/eee560/spacerad. html [Retrieved: December 2010]

[13] Prolss GW. Physics of the Earth's Space Environment. Berlin, Heidelberg,

[14] Gopalswamy N. Coronal mass ejections and space weather. In: Tsuda T, Fuji R, Shibata K, Geller MA, editors. Climate and Weather of the Sun-Earth System (CAWSES): Selected Paper from the 2007 Kyoto Symposium; 2009.

[15] Mewalt RA. Cosmic Ray. 1996. Available from: http://www.srl.caltech. edu/personnel/dick/cos\_encyc.html

[16] Adams L. Space Radiation Effects in Electronic Components. PA and

Germany: Springer; 2004

pp. 77-120

[Retrieved: July 2019]

Solar experts predict the Sun's activity in Solar Cycle 25 to be below average, similar to Solar Cycle 24. National Oceanic and Atmospheric Administration (NOAA). Online

of Engineering (RAE); 2013

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

[1] Nwankwo VJN. Determination of the stopping power and failure time of spacecraft components due to proton (e+) interaction using GOES 11 acquisition data [M.Sc. thesis]. Ibadan, Nigeria: University of Ibadan; 2010

[2] Jibiri NN, Nwankwo VUJ, Kio M. Determination of the stopping power and failure time of spacecraft components due to proton interaction using GOES 11 acquisition data. International Journal of Engineering, Science and Technology.

[3] Iucci N, Levitin AE, Belov AV,

[4] Shea MA, Smart DF, Allen JH, Wilkinson DL. Spacecraft problems in association with episodes of intense solar activity and related terrestrial phenomena during March 1991. IEEE Transactions on Nuclear Science.

[5] Bedingfield KL, Leach RD, Alexander MB, editors. Spacecraft System Failures and Anomalies Attributed to Natural Space

MSFC, Alabama 35812; 1996

Weather. 2015;**13**:484-502

[8] RAE. Extreme Space Weather: Impacts on Engineered Systems and

Environment. NASA REF-1390. NASA-

[6] Martin G. SumbandilaSat beyond repair. Defence Web. 2012. Available from: https://www.defenceweb.co.za/ joint/science-a-defence-technology/ sumbandilasat-beyond-repair/ [Retreived: 20 May 2019]

[7] Loto'aniu TM, Singer HJ, Rodriguez JV, Green J, Denig W, Biesecker D, et al. Space weather conditions during the Galaxy 15 spacecraft anomaly. Space

Eroshenko EA, Ptitsyna NG, Villoresi G, et al. Space weather conditions and spacecraft anomalies in different orbits. Space Weather. 2005;**3**:1-16. S01001

**References**

2011;**3**:6532-6542

1992;**39**:1754-1760

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

#### **References**

*Satellites Missions and Technologies for Geosciences*

that this review (on the space radiation effects on satellites and their mitigation methods) is succinct when compared to the large body of work in the subject area. Therefore, we encourage readers to also consult other well-accomplished texts for

specific space radiation effect and the appropriate mitigation approach.

**86**

**Author details**

Victor U.J. Nwankwo1

Ibadan, Ibadan, Nigeria

\*, Nnamdi N. Jibiri2

of Physics, Anchor University, Lagos, Nigeria

\*Address all correspondence to<EMAIL_ADDRESS>
Development Agency, Abuja, Nigeria

provided the original work is properly cited.

and Michael T. Kio3

1 Space, Atmospheric Physics and Radio Wave Propagation Laboratory, Department

2 Radiation and Health Physics Laboratory, Department of Physics, University of

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

3 Engineering and Space Systems Department, National Space and Research

[1] Nwankwo VJN. Determination of the stopping power and failure time of spacecraft components due to proton (e+) interaction using GOES 11 acquisition data [M.Sc. thesis]. Ibadan, Nigeria: University of Ibadan; 2010

[2] Jibiri NN, Nwankwo VUJ, Kio M. Determination of the stopping power and failure time of spacecraft components due to proton interaction using GOES 11 acquisition data. International Journal of Engineering, Science and Technology. 2011;**3**:6532-6542

[3] Iucci N, Levitin AE, Belov AV, Eroshenko EA, Ptitsyna NG, Villoresi G, et al. Space weather conditions and spacecraft anomalies in different orbits. Space Weather. 2005;**3**:1-16. S01001

[4] Shea MA, Smart DF, Allen JH, Wilkinson DL. Spacecraft problems in association with episodes of intense solar activity and related terrestrial phenomena during March 1991. IEEE Transactions on Nuclear Science. 1992;**39**:1754-1760

[5] Bedingfield KL, Leach RD, Alexander MB, editors. Spacecraft System Failures and Anomalies Attributed to Natural Space Environment. NASA REF-1390. NASA-MSFC, Alabama 35812; 1996

[6] Martin G. SumbandilaSat beyond repair. Defence Web. 2012. Available from: https://www.defenceweb.co.za/ joint/science-a-defence-technology/ sumbandilasat-beyond-repair/ [Retreived: 20 May 2019]

[7] Loto'aniu TM, Singer HJ, Rodriguez JV, Green J, Denig W, Biesecker D, et al. Space weather conditions during the Galaxy 15 spacecraft anomaly. Space Weather. 2015;**13**:484-502

[8] RAE. Extreme Space Weather: Impacts on Engineered Systems and Infrastructure. London: Royal Academy of Engineering (RAE); 2013

[9] Allen JH, Wilkinson D. Spacecraft charging: Then and now. In: Spacecraft charging technology conference, Albuquerque, NM, 20-24 September 2010

[10] National Weather Service (NWS). Solar experts predict the Sun's activity in Solar Cycle 25 to be below average, similar to Solar Cycle 24. National Oceanic and Atmospheric Administration (NOAA). Online Resource; 2019

[11] The National Academies of Sciences, Engineering and Medicine. Testing at the speed of light: The State of U.S. In: Electronic Parts Space Radiation Testing Infrastructure. Washington, DC: The National Academic Press; 2018. DOI: 10.17226/24993

[12] Holbert KE. Space Radiation Environmental Effects. Courses in Electrical Engineering, Arizona State University. 2007. Available from: http:// holbert.faculty.asu.edu/eee560/spacerad. html [Retrieved: December 2010]

[13] Prolss GW. Physics of the Earth's Space Environment. Berlin, Heidelberg, Germany: Springer; 2004

[14] Gopalswamy N. Coronal mass ejections and space weather. In: Tsuda T, Fuji R, Shibata K, Geller MA, editors. Climate and Weather of the Sun-Earth System (CAWSES): Selected Paper from the 2007 Kyoto Symposium; 2009. pp. 77-120

[15] Mewalt RA. Cosmic Ray. 1996. Available from: http://www.srl.caltech. edu/personnel/dick/cos\_encyc.html [Retrieved: July 2019]

[16] Adams L. Space Radiation Effects in Electronic Components. PA and

Safety Office, Brunel University. 2003. Available from: http://paso.esa. int/5\_training…/training\_03\_space%20 radiation.ppt [Retrieved: March 2010]

[17] Mikaelian T. Spacecraft Charging and Hazards to Electronics in Space. York University Publication; 2001. arXiv:0906.3884; 2009

[18] Shaw RR, Nanevicz JE, Adamo RC. Observation of electrical discharges caused by differential satellite charging by magnetospheric plasmas. In: Rosen A, editor. Spacecraft Charging by Magnetospheric Plasma. Progress in Astronautics and Aeronautics. Vol. 47. 1976. pp. 61-76

[19] Leach RD, Alexander MB. Failure and Anomalies Attributed to Spacecraft Charging. AL: NASA RP-1375 Marshall Space Flight Centre; 1995

[20] Gussenhoven MS, Mullen EG, Brautigam DH. Improved understanding of the Earth's radiation belts from the CRRES satellite. IEEE Transactions on Nuclear Science. 1996;**43**(2):353-368

[21] Sayyah R, Macleod TC, Ho FD. Radiation-hardened electronics and ferroelectric memory for space flight systems. Ferroelectrics. 2011;**413**:170-175

[22] Nichols DK, Coss JR, Watson RK, Schwartz HR, Pease RL. An observation of proton-induced latchup. IEEE Transactions on Nuclear Science. 1992;**39**(6):1654-1656

[23] Mouret I, Allenspach M, Schrimpf RD, Brews JR, Galloway KF, Calvel P. Temperature and angular dependence of substrate response in SEGR. IEEE Transactions on Nuclear Science. 1994;**41**(6):2216-2221

[24] Adams JH, Gelman A. The effects of solar flares on single event upset rates.

IEEE Transactions on Nuclear Science. 1984;**39**(6):1212-1216

[25] Campbell AB. SEU flight data from CRRES MEP. IEEE Transactions on Nuclear Science. 1991;**38**(6):1647-1654

[26] Oldham TR, McLean FB. Total ionizing dose in MOS oxides and devices. IEEE Transactions on Nuclear Science. 2003;**50**(3)

[27] Srour JR, Marshall CJ, Marshall PW. Review of displacement damage effects in silicon devices. IEEE Transactions on Nuclear Science. 2003;**50**:653-670

[28] Getachew A. Stopping Power and Range of Protons of Various Energies in Different Materials [M.Sc. thesis]. Ethiopia: Department of Physics, Addis Ababa University; 2007

[29] Garrett HB. Space Weather Impacts on Spacecrafts and Mitigation Strategies. California, USA, Pasadena, CA, USA: Jet Propulsion Laboratory, California Institute of Technology; 2012

[30] Lai ST. A critical overview on spacecraft charging control method. In: 6th Spacecraft Charging Technology Conference, AFRL-VS-TR-20001578; 2000

[31] Lai ST, Cahoy K. Spacecraft charging. In: Encyclopedia of Plasma Technology. Taylor & Francis; 2017. DOI: 10.1081/E-EPLT-120053644

[32] Maurer RH, Fraeman ME, Martin MN, Roth DR. Harsh environments: Space radiation environment, effects and mitigation. Johns Hopkins APL Technical Digest. 2008;**28**:17-29

[33] Shepherd SM. Spacecraft shielding. Online lecture series, Thayer Scholl of Engineering at Dartmouth College [Retrieved: October 2019]

**89**

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space*

[42] Nwankwo VUJ. Effects of space weather on Earth's ionosphere and nominal LEO satellites' aerodynamic drag [PhD thesis]. Kolkata, India: University of Calcutta; 2016

*DOI: http://dx.doi.org/10.5772/intechopen.90115*

[34] ReliaSoft Corporation. Reliability Basics. Reliability HotWire e-Magazine. HBM Prenscia Inc. Weibull.com;

[35] Nwankwo VUJ, Chakrabarti SK, Weigel RS. Effects of plasma drag on low earth orbiting satellites due to solar forcing induced perturbations and heating. Advances in Space Research.

[36] Baker DN, Erickson PJ, Fennell JF, Foster JC, Jaynes AN, Verronen PT. Space weather effects in the Earth's radiation belts. Space Science Reviews. 2017;**214**:17

[37] Hapgood and Thomson (for Lloyd's 360° Risk Insight). Space Weather: It's Impact on Earth and Implications for Business. London: RAL Space; 2010

[38] Nwankwo VUJ, Chakrabarti KS. Theoretical modeling of drag force impact on a model international space station (ISS) during variation of solar activity. Transactions of JSASS, Aerospace

Technology Japan. 2014;**12**:47-53

perturbations on trans-Martian trajectory of Mars missions before Mars orbit insertion. Indian Journal of

[40] Nwankwo VUJ, Chakrabarti S. Effects of space weather on the ionosphere and LEO satellites orbital trajectory in the equatorial, low and mid-latitude regions. Advances in Space

[41] Nwankwo VUJ. Space weather: Responses of the atmosphere to solar activity and its implications for LEO satellites aerodynamic drag. In: Mukhopadhyay B, Sasmal S, editors. Exploring the Universe: From Near Space to Extra-Galactic. Springer International Publishing, Springer Nature Switzerland AG; 2018

Physics. 2015;**89**:1235-1245

Research. 2018;**61**:1880-1889

[39] Nwankwo VUJ, Chakrabarti SK. Analysis of planetary and solar induced

2008

2015;**56**:47-56

*The Impact of Space Radiation Environment on Satellites Operation in Near-Earth Space DOI: http://dx.doi.org/10.5772/intechopen.90115*

[34] ReliaSoft Corporation. Reliability Basics. Reliability HotWire e-Magazine. HBM Prenscia Inc. Weibull.com; 2008

*Satellites Missions and Technologies for Geosciences*

IEEE Transactions on Nuclear Science.

[25] Campbell AB. SEU flight data from CRRES MEP. IEEE Transactions on Nuclear Science. 1991;**38**(6):1647-1654

[26] Oldham TR, McLean FB. Total ionizing dose in MOS oxides and devices. IEEE Transactions on Nuclear

Marshall PW. Review of displacement damage effects in silicon devices. IEEE Transactions on Nuclear Science.

[28] Getachew A. Stopping Power and Range of Protons of Various Energies in Different Materials [M.Sc. thesis]. Ethiopia: Department of Physics, Addis

1984;**39**(6):1212-1216

Science. 2003;**50**(3)

2003;**50**:653-670

Ababa University; 2007

2000

[29] Garrett HB. Space Weather Impacts on Spacecrafts and Mitigation Strategies. California, USA, Pasadena, CA, USA: Jet Propulsion Laboratory, California Institute of Technology; 2012

[30] Lai ST. A critical overview on spacecraft charging control method. In: 6th Spacecraft Charging Technology Conference, AFRL-VS-TR-20001578;

[31] Lai ST, Cahoy K. Spacecraft charging. In: Encyclopedia of Plasma Technology. Taylor & Francis; 2017. DOI: 10.1081/E-EPLT-120053644

[32] Maurer RH, Fraeman ME, Martin MN, Roth DR. Harsh environments: Space radiation environment, effects and mitigation. Johns Hopkins APL Technical Digest.

[Retrieved: October 2019]

[33] Shepherd SM. Spacecraft shielding. Online lecture series, Thayer Scholl of Engineering at Dartmouth College

2008;**28**:17-29

[27] Srour JR, Marshall CJ,

Safety Office, Brunel University. 2003. Available from: http://paso.esa. int/5\_training…/training\_03\_space%20 radiation.ppt [Retrieved: March 2010]

[17] Mikaelian T. Spacecraft Charging and Hazards to Electronics in Space. York University Publication; 2001.

Adamo RC. Observation of electrical discharges caused by differential satellite charging by magnetospheric plasmas. In: Rosen A, editor. Spacecraft

Plasma. Progress in Astronautics and Aeronautics. Vol. 47. 1976. pp. 61-76

[19] Leach RD, Alexander MB. Failure and Anomalies Attributed to Spacecraft Charging. AL: NASA RP-1375 Marshall

[20] Gussenhoven MS, Mullen EG,

[21] Sayyah R, Macleod TC, Ho FD. Radiation-hardened electronics and ferroelectric memory for space flight systems. Ferroelectrics.

[22] Nichols DK, Coss JR, Watson RK, Schwartz HR, Pease RL. An observation of proton-induced latchup. IEEE Transactions on Nuclear Science.

Schrimpf RD, Brews JR, Galloway KF, Calvel P. Temperature and angular dependence of substrate response in SEGR. IEEE Transactions on Nuclear Science. 1994;**41**(6):2216-2221

[24] Adams JH, Gelman A. The effects of solar flares on single event upset rates.

understanding of the Earth's radiation belts from the CRRES satellite. IEEE Transactions on Nuclear Science.

arXiv:0906.3884; 2009

[18] Shaw RR, Nanevicz JE,

Charging by Magnetospheric

Space Flight Centre; 1995

Brautigam DH. Improved

1996;**43**(2):353-368

2011;**413**:170-175

1992;**39**(6):1654-1656

[23] Mouret I, Allenspach M,

**88**

[35] Nwankwo VUJ, Chakrabarti SK, Weigel RS. Effects of plasma drag on low earth orbiting satellites due to solar forcing induced perturbations and heating. Advances in Space Research. 2015;**56**:47-56

[36] Baker DN, Erickson PJ, Fennell JF, Foster JC, Jaynes AN, Verronen PT. Space weather effects in the Earth's radiation belts. Space Science Reviews. 2017;**214**:17

[37] Hapgood and Thomson (for Lloyd's 360° Risk Insight). Space Weather: It's Impact on Earth and Implications for Business. London: RAL Space; 2010

[38] Nwankwo VUJ, Chakrabarti KS. Theoretical modeling of drag force impact on a model international space station (ISS) during variation of solar activity. Transactions of JSASS, Aerospace Technology Japan. 2014;**12**:47-53

[39] Nwankwo VUJ, Chakrabarti SK. Analysis of planetary and solar induced perturbations on trans-Martian trajectory of Mars missions before Mars orbit insertion. Indian Journal of Physics. 2015;**89**:1235-1245

[40] Nwankwo VUJ, Chakrabarti S. Effects of space weather on the ionosphere and LEO satellites orbital trajectory in the equatorial, low and mid-latitude regions. Advances in Space Research. 2018;**61**:1880-1889

[41] Nwankwo VUJ. Space weather: Responses of the atmosphere to solar activity and its implications for LEO satellites aerodynamic drag. In: Mukhopadhyay B, Sasmal S, editors. Exploring the Universe: From Near Space to Extra-Galactic. Springer International Publishing, Springer Nature Switzerland AG; 2018

[42] Nwankwo VUJ. Effects of space weather on Earth's ionosphere and nominal LEO satellites' aerodynamic drag [PhD thesis]. Kolkata, India: University of Calcutta; 2016

**Chapter 6**

**Abstract**

Needs and Tricks

*Shishir Priyadarshi*

measure of scintillation indices.

**1. Introduction**

**91**

**Keywords:** ionospheric scintillation, empirical scintillation model, GPS/GNSS scintillation modeling, global scintillation model

Whenever the radio-wave signals pass through the ionospheric irregularities, these signals feel reflection, refraction, and scintillations (i.e., sharp and rapid carrier-phase variations and signal-to-noise ratio fading). In general it is more typical when the carrier-phase loss of lock happens due to the sharp signal-to-noise ratio fading ([1, 2] and references therein). As the wave propagates to the ground, scintillation models are needed to produce global as well as local ionospheric scintillation data and maps during the required solar activity condition, day, season, and geographic locations. Generally, scintillation models are made to serve special needs and not for all the spatial and temporal situations; due to this generally each scintil-

lation model is not fit for all the geographic and solar activity conditions.

In general, scintillation models often have two significant limitations; firstly physics-based models often fail in producing scintillation morphology during

Ionospheric Scintillation Modeling

The wavelength of the radio-wave satellite signal is of the order of the minimal small-scale ionospheric irregularities (i.e., a few centimeters). As the satellite signal passes through the ionosphere, its interaction with the ionospheric irregularity structures causes refraction, reflection, and polarization in the satellite signal. Ionospheric irregularities degrade the trans-ionospheric radio-wave signal quality, between the satellite and the receivers, due to scintillation. The physics-based model often fails to produce global morphology during the extreme solar events, whereas empirical models based on the ionospheric scintillation data demonstrate better quality to forecast the scintillation effects during extreme solar event. It is really tricky to make a scintillation model that is sensitive to low and high solar activities as well as extreme solar events simultaneously. In the presented book chapter, we will discuss/review the needs and tricks of modeling ionospheric scintillation during extreme solar events as well as all weather and latitudinal cases. There are several aspects that influence the scintillation occurrence, its strength, and global distribution. The latitudinal dependence, local weather, solar/geomagnetic activity conditions, and local times are the widely accepted factors that control and influence ionospheric scintillation most. This book chapter discusses all these aspects and also suggests the ways to cast aside those factors that led to the wrong

#### **Chapter 6**

## Ionospheric Scintillation Modeling Needs and Tricks

*Shishir Priyadarshi*

#### **Abstract**

The wavelength of the radio-wave satellite signal is of the order of the minimal small-scale ionospheric irregularities (i.e., a few centimeters). As the satellite signal passes through the ionosphere, its interaction with the ionospheric irregularity structures causes refraction, reflection, and polarization in the satellite signal. Ionospheric irregularities degrade the trans-ionospheric radio-wave signal quality, between the satellite and the receivers, due to scintillation. The physics-based model often fails to produce global morphology during the extreme solar events, whereas empirical models based on the ionospheric scintillation data demonstrate better quality to forecast the scintillation effects during extreme solar event. It is really tricky to make a scintillation model that is sensitive to low and high solar activities as well as extreme solar events simultaneously. In the presented book chapter, we will discuss/review the needs and tricks of modeling ionospheric scintillation during extreme solar events as well as all weather and latitudinal cases. There are several aspects that influence the scintillation occurrence, its strength, and global distribution. The latitudinal dependence, local weather, solar/geomagnetic activity conditions, and local times are the widely accepted factors that control and influence ionospheric scintillation most. This book chapter discusses all these aspects and also suggests the ways to cast aside those factors that led to the wrong measure of scintillation indices.

**Keywords:** ionospheric scintillation, empirical scintillation model, GPS/GNSS scintillation modeling, global scintillation model

#### **1. Introduction**

Whenever the radio-wave signals pass through the ionospheric irregularities, these signals feel reflection, refraction, and scintillations (i.e., sharp and rapid carrier-phase variations and signal-to-noise ratio fading). In general it is more typical when the carrier-phase loss of lock happens due to the sharp signal-to-noise ratio fading ([1, 2] and references therein). As the wave propagates to the ground, scintillation models are needed to produce global as well as local ionospheric scintillation data and maps during the required solar activity condition, day, season, and geographic locations. Generally, scintillation models are made to serve special needs and not for all the spatial and temporal situations; due to this generally each scintillation model is not fit for all the geographic and solar activity conditions.

In general, scintillation models often have two significant limitations; firstly physics-based models often fail in producing scintillation morphology during

extreme solar and geomagnetic events. The second limitation is there is no possibility of a correction in the model once its algorithm is derived. In the presented book chapter, scintillation empirical modeling methods and their limitations are discussed. Geometrical effects contaminate scintillation observations most. We have discussed in this chapter how to overcome scintillation modeling limitations and use some tricks that replicate the actual scintillation morphology. The presented text in this chapter will enrich the knowledge of ionospheric modelers and make them understand how beginners should proceed with the ionospheric scintillation or ionospheric electron density as a model input data, if they decided to model certain ionospheric parameters (such as spectral index, turbulence strength parameters of the ionospheric irregularities, amplitude and phase fluctuations, scintillation indices, etc.).

should always keep in mind that their algorithm should be sensitive to the geographic locations, solar activity as well as local weather. This can be achieved by having different derivation algorithm for each and every geographic location, and the final algorithm should combine all these sub-algorithm to demonstrate the

It is better to have the latest data for modeling new events, but, in case of new data unavailability, the previous data may be from the previous solar cycle [6]. The latest data are generally close to the new solar/or geomagnetic event, and they are from the same solar cycle activity period. Therefore, the scintillation models based on the latest data are comparatively closer to the new observations in comparison to the data from the previous solar cycles. The advent of scintillation effect on the trans-ionospheric radio-wave signal lower elevation angles (≤ 20°) is being

discarded from the data to minimize the effect of multipath. Multipath can occur on any elevation angle. To reduce the high-elevation angle, multipath scintillation receiver's antenna must be setup to minimize CODE and PHASE reflections

(multipath), by mounting it away from close reflecting surfaces [6]. The multipath effect also depends on the PRN code rate (please see [7] for details). Moreover the multipath effect can appear at higher elevation angles than 20° (please see [8] for details). Multipath effects occurring at any elevation can be minimized by the geometrical corrections in the data [2]. But, to do it one should be well familiar with the other high-altitude structures (such as mountains or high-altitude building, etc.) near the GPS/GNSS receivers' location and filter the datasets reflected from such structures to reduce the multipath effect. To avoid the high-altitude structures, we have to manual check the data and avoid those elevation angles which show unusual enhancement in the scintillation indices. Following Rino [9], ionospheric irregularities orient themselves according to the local geomagnetic field lines. The phase lock loss highly depends on the angle between the geomagnetic field lines and receiver-transmitter line of sight [10, 11]. For example, at the polar ionosphere, ionospheric irregularities often form rodlike structure and orient themselves along the vertical geomagnetic field lines, whereas at the mid and equatorial latitudes, the local geomagnetic field line is merely horizontal to the Earth's surface due to which sheet- or winglike ionospheric irregularity structures frequently appear. If the irregularity orientations are along the geomagnetic field lines, they form a rodlike structure; if the ionospheric irregularity orientation is across the geomagnetic field lines, it may appear either as a wing- or as a sheetlike structure. We are addressing both cases (rodlike structure and the high-latitude and sheet-/winglike structure at

Following Rino [9] and Booker [12], phase and amplitude scintillations can be

where re is the classical electron radius; λ is the wavelength of the signal; L is the

*q*�2*ϑ*þ1 0 Γ *υ* � 1

> 4*πΓ υ* þ 1 2

> > 2 � �

2 � �

*π* p Γð Þ ð Þ *υ* þ 0*:*5 *=*2 ð Þ *υ* � 0*:*5 *ℊ F a*ð Þ *; b* (2)

� � *F a*ð Þ *; b* (1)

ð Þ *Lsecθ GCs*

2 ffiffiffi

irregularity slab thickness; θ is the satellite zenith angle; Cs is the turbulence strength parameter, which is a function of the fluctuation in the electron density (ΔN/N) in the irregularity slab along the satellite signal path; G is the geometric

ð Þ *Lsecθ CsZυ*�1*=*2 Γ 2*:*5�*υ*

**2.2 Geometrical error correction and lower elevation multipath**

the equatorial and mid-latitude) in this book chapter.

> ¼ *r* 2 *e λ*2

< *δφ*2

expressed as follows:

*S*2 4 ¼ *r* 2 *e λ*2

**93**

global scintillation response.

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

#### **2. Scintillation modeling tricks and correction for the geometry of propagation**

As the elevation angle of the signal wave source changes, we observe the changes in the intensity of ionospheric scintillation. Such changes are significant as they are caused due to enhancement in the path of the radio-wave signal through the ionospheric irregularity layer with decreasing elevation angle and vice versa [3]. The signal ray path through the ionospheric irregularity also depends on the size and orientation of the ionospheric irregularity structure along with the height and thickness of the ionospheric irregularity layer [1]. All these elements influence the intensity of the ionospheric scintillation, and the effect caused by them on the transionospheric radio-wave is termed as the geometrical effect [3–5]. In this section, we will cover the scintillation modeling tricks and method to minimize the multipath effect and impact ways to overcome other geometrical effects such as irregularity orientation with respect to the local geomagnetic field lines, multipath at higher elevation angle, radio-wave signals' extended path near the Earth's horizon, etc.

#### **2.1 Scintillation modeling tricks**

For the empirical scintillation modeling, first, we should need to have data for all the seasons and solar as well as geomagnetic activity situation. For instance, if we are planning to model ionospheric scintillation during high solar activity in winter months, we must have winter-month data collected during high solar activity period. Similarly, for the low solar activity period and in particular month scintillation modeling, we must have alike data. An adequate empirical modeling study expands understanding of ionospheric irregularities and can be used to better evaluate the impact of scintillation on different resources. The physics-based model often fails to produce global morphology during extreme solar events, whereas empirical models based on the ionospheric scintillation data demonstrate better scintillation effects during extreme solar events. It is really tricky to make a scintillation model which is sensitive to low and high solar activities as well as extreme solar events simultaneously.

The modeler should also derive the relationship between solar activity and provisional activity indices with the ionospheric scintillation data in order to make the scintillation data sensitive to the solar activity condition. One should always keep in mind that all the solar activity, geomagnetic, and provisional indices are not equally beneficial to all the geographic locations. Therefore, one should use the proper geo, solar, and provisional activity indices for specific geographic locations. If the modeler is planning to develop a global ionospheric scintillation model, they

extreme solar and geomagnetic events. The second limitation is there is no possibility of a correction in the model once its algorithm is derived. In the presented book

chapter, scintillation empirical modeling methods and their limitations are discussed. Geometrical effects contaminate scintillation observations most. We have discussed in this chapter how to overcome scintillation modeling limitations and use some tricks that replicate the actual scintillation morphology. The presented text in this chapter will enrich the knowledge of ionospheric modelers and make them understand how beginners should proceed with the ionospheric scintillation or ionospheric electron density as a model input data, if they decided to model certain ionospheric parameters (such as spectral index, turbulence strength parameters of the ionospheric irregularities, amplitude and phase fluctuations,

**2. Scintillation modeling tricks and correction for the geometry**

As the elevation angle of the signal wave source changes, we observe the changes in the intensity of ionospheric scintillation. Such changes are significant as they are caused due to enhancement in the path of the radio-wave signal through the ionospheric irregularity layer with decreasing elevation angle and vice versa [3]. The signal ray path through the ionospheric irregularity also depends on the size and orientation of the ionospheric irregularity structure along with the height and thickness of the ionospheric irregularity layer [1]. All these elements influence the intensity of the ionospheric scintillation, and the effect caused by them on the transionospheric radio-wave is termed as the geometrical effect [3–5]. In this section, we will cover the scintillation modeling tricks and method to minimize the multipath effect and impact ways to overcome other geometrical effects such as irregularity orientation with respect to the local geomagnetic field lines, multipath at higher elevation angle, radio-wave signals' extended path near the Earth's horizon, etc.

For the empirical scintillation modeling, first, we should need to have data for all the seasons and solar as well as geomagnetic activity situation. For instance, if we are planning to model ionospheric scintillation during high solar activity in winter months, we must have winter-month data collected during high solar activity period. Similarly, for the low solar activity period and in particular month scintillation modeling, we must have alike data. An adequate empirical modeling study expands understanding of ionospheric irregularities and can be used to better evaluate the impact of scintillation on different resources. The physics-based model often fails to produce global morphology during extreme solar events, whereas empirical models based on the ionospheric scintillation data demonstrate better scintillation effects during extreme solar events. It is really tricky to make a scintillation model which is sensitive to low and high solar activities as well as

The modeler should also derive the relationship between solar activity and provisional activity indices with the ionospheric scintillation data in order to make the scintillation data sensitive to the solar activity condition. One should always keep in mind that all the solar activity, geomagnetic, and provisional indices are not equally beneficial to all the geographic locations. Therefore, one should use the proper geo, solar, and provisional activity indices for specific geographic locations. If the modeler is planning to develop a global ionospheric scintillation model, they

scintillation indices, etc.).

*Satellites Missions and Technologies for Geosciences*

**of propagation**

**2.1 Scintillation modeling tricks**

extreme solar events simultaneously.

**92**

should always keep in mind that their algorithm should be sensitive to the geographic locations, solar activity as well as local weather. This can be achieved by having different derivation algorithm for each and every geographic location, and the final algorithm should combine all these sub-algorithm to demonstrate the global scintillation response.

#### **2.2 Geometrical error correction and lower elevation multipath**

It is better to have the latest data for modeling new events, but, in case of new data unavailability, the previous data may be from the previous solar cycle [6]. The latest data are generally close to the new solar/or geomagnetic event, and they are from the same solar cycle activity period. Therefore, the scintillation models based on the latest data are comparatively closer to the new observations in comparison to the data from the previous solar cycles. The advent of scintillation effect on the trans-ionospheric radio-wave signal lower elevation angles (≤ 20°) is being discarded from the data to minimize the effect of multipath. Multipath can occur on any elevation angle. To reduce the high-elevation angle, multipath scintillation receiver's antenna must be setup to minimize CODE and PHASE reflections (multipath), by mounting it away from close reflecting surfaces [6]. The multipath effect also depends on the PRN code rate (please see [7] for details). Moreover the multipath effect can appear at higher elevation angles than 20° (please see [8] for details). Multipath effects occurring at any elevation can be minimized by the geometrical corrections in the data [2]. But, to do it one should be well familiar with the other high-altitude structures (such as mountains or high-altitude building, etc.) near the GPS/GNSS receivers' location and filter the datasets reflected from such structures to reduce the multipath effect. To avoid the high-altitude structures, we have to manual check the data and avoid those elevation angles which show unusual enhancement in the scintillation indices. Following Rino [9], ionospheric irregularities orient themselves according to the local geomagnetic field lines. The phase lock loss highly depends on the angle between the geomagnetic field lines and receiver-transmitter line of sight [10, 11]. For example, at the polar ionosphere, ionospheric irregularities often form rodlike structure and orient themselves along the vertical geomagnetic field lines, whereas at the mid and equatorial latitudes, the local geomagnetic field line is merely horizontal to the Earth's surface due to which sheet- or winglike ionospheric irregularity structures frequently appear. If the irregularity orientations are along the geomagnetic field lines, they form a rodlike structure; if the ionospheric irregularity orientation is across the geomagnetic field lines, it may appear either as a wing- or as a sheetlike structure. We are addressing both cases (rodlike structure and the high-latitude and sheet-/winglike structure at the equatorial and mid-latitude) in this book chapter.

Following Rino [9] and Booker [12], phase and amplitude scintillations can be expressed as follows:

$$<\delta\rho^2> = r\_\epsilon^2 \lambda^2 (Lsec\theta) G C\_t \frac{q\_0^{-2\theta+1} \Gamma\left(\nu - \frac{1}{2}\right)}{4\pi \Gamma\left(\nu + \frac{1}{2}\right)} F(a, b) \tag{1}$$

$$\mathbf{S}\_4^2 = r\_\epsilon^2 \lambda^2 (\mathbf{L} \sec \theta) \mathbf{C}\_\imath \mathbf{Z}^{\nu - 1/2} \frac{\Gamma \left( \frac{2.5 - \nu}{2} \right)}{2 \sqrt{\pi} \Gamma((\nu + 0.5)/2)(\nu - 0.5)} \, g \, F(a, b) \tag{2}$$

where re is the classical electron radius; λ is the wavelength of the signal; L is the irregularity slab thickness; θ is the satellite zenith angle; Cs is the turbulence strength parameter, which is a function of the fluctuation in the electron density (ΔN/N) in the irregularity slab along the satellite signal path; G is the geometric

on a moving object such as vehicles, ships, or airplanes; onboard at any beacon satellites; or on a spacecraft. The geometrical effect is highly dependent on the elevation angle at which the receiver receives the satellite signal, azimuth angle of the receiver, and orientation of the ionospheric irregularity structures with respect to the local geomagnetic field. The geometrical effects also depend on the angle between the signal ray path and the local geomagnetic field. Another important aspect that influences the scintillation morphology and the rate is the combination of several things such as the geographic location of our region of interest, local season, local time, solar activity condition, during a geomagnetic quite day or a geomagnetically disturbed day, etc. Here first we will discuss in details the geometrical influence on the ionospheric scintillation using the illustrative examples and demonstrate the influence of the geometrical correction on the satellite signal.

**3.1 Influence of the geometrical effects over the scintillation estimation and the**

In Eq. (1) the height of the ionospheric irregularity from the Earth's surface Z is a function of sec(θ). The zenith angle (θ) is a function of elevation angle (E) and

Using the relation between satellite and zenith angle, Eq. (2) can be simplified as

As we mentioned earlier, υ is a three-dimensional ionospheric irregularity spec-

S4 � sec 90 ð Þ � E sec 90 ð Þ � E υ�1*=*2 h i1*=*2

dimensional spectral index as p = 2υ�1. If we simplify Eqs. (3) and (4), we will get to a direct dependence relationship between scintillation indices and zenith angle. Following Priyadarshi and Wernik [13], we can derive the spectral index p by using the log-log relationship of the scintillation index observation and cosecant of the

From Eq. (5) it is clear that the scintillation index is a power-law function of cosecant of the elevation angle with the power one-dimensional ionospheric irregularity spectral index (p) [13]. In order to simplify it more and avoid the dependence on the filter factor F(a,b), which is a complicated function of the ionospheric irregularity elongation parameters and which makes the overall ionospheric irregularity orientation dependence very complicated [13], we have considered the ionospheric radio-wave propagation environment as isotropic [9], and this turns F(a, b) = 1. Now if we plot log-log maps for S4 and Sin (E) angle, we can calculate the one-dimensional spectra index (p) from this relationship. Once we have spectral index, we can correct the scintillation for the geometry of propagation between the

**Figure 1** shows the non-corrected (S4\_observed) Vs-corrected scintillation indices (S4\_corrected) observed from the GPS scintillation receiver GSV 4004b deployed at

tral index [9]. One-dimensional spectral index (p) is related to the three-

θ ¼ 90 � E (3)

*S*4 � cscð Þ *E* ð Þ *p*þ2 *=*4 F að Þ *;* b (5)

S4\_corrected ¼ S4\_observed*=*csc Eð Þð Þ Pþ2 *=*4 (6)

(4)

**way to remove these errors**

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

can be expressed as

satellite elevation angle [13]:

**95**

receiver and the transmitter using the Eq. (6):

**Table 1.**

*Form of the ionospheric irregularities.*

factor and is a function of ionospheric irregularity elongation parameters F(a,b), "a" is the elongation parameter of the irregularities along the filed lines and "b" is used for elongation across the geomagnetic field lines; υ is the three-dimensional spectral index; q0 is the inner scale constant and Z ➔*λZRSecθ* 4*π* ; ZR = ZZs/(Z + Zs) and Zs are the distance to the source; *ℊ* is the common geometry and propagation factor, which is also a function of elongation parameters a and b; and <*δφ*2> is the phase variance in the satellite signal after passing through the ionospheric irregularity.

Following the assumption of the theory of wave propagation in random medium, it is safe to assume at the signal frequency of interest that only the phase of the signal wave gets distorted [2] as the signal passes through the ionospheric irregularity of slab thickness L, and GPS scintillation receivers can observe the time series of the phase-modulated signal on the ground. Formulas (1) and (2) can be used to simulate the amplitude and phase scintillation. Study of the power spectrum of the ionospheric data improves the estimation of the local ionospheric irregularity form and their orientation with respect to the local geomagnetic field. Several ionospheric parameters such us spectral index, turbulence strength parameter, and phase fluctuations are essential for correcting the data contaminated through the geometrical errors.

Following Eq. (2) discussed in Rino [9], scintillation index is a function of Fresnel filter factor F(a,b) which is a function of elongation parameters "a" and "b." A detailed explanation of this function is discussed in Rino [9]; as it is beyond the scope of this book chapter therefore we are not discussing it in more details. But, for the reader's convenience, we are providing a summary table (please see **Table 1**), which summarizes the different combinations of "a" and "b" giving rise to different ionospheric irregularity shapes.

#### **3. Scintillation modeling needs and discussions**

Scintillation modeling provides a general scenario of the ionospheric scintillations' global morphology and occurrence during different solar activity and space weather conditions. It is always not possible to obtain ionospheric scintillation observation during some space weather events, and during such situations, a realistic ionospheric scintillation model can be used to fill the data gaps. On the other hand, data assimilation techniques also use scintillation model to assimilate scintillation observation into the scintillation model in order to improve the forecast.

There are two aspects that influence the occurrence and strength of the ionospheric scintillation. First is the geometrical effect between the radio-wave-emitting satellite and the receiver which can be at any different location, e.g., at the ground;

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

on a moving object such as vehicles, ships, or airplanes; onboard at any beacon satellites; or on a spacecraft. The geometrical effect is highly dependent on the elevation angle at which the receiver receives the satellite signal, azimuth angle of the receiver, and orientation of the ionospheric irregularity structures with respect to the local geomagnetic field. The geometrical effects also depend on the angle between the signal ray path and the local geomagnetic field. Another important aspect that influences the scintillation morphology and the rate is the combination of several things such as the geographic location of our region of interest, local season, local time, solar activity condition, during a geomagnetic quite day or a geomagnetically disturbed day, etc. Here first we will discuss in details the geometrical influence on the ionospheric scintillation using the illustrative examples and demonstrate the influence of the geometrical correction on the satellite signal.

#### **3.1 Influence of the geometrical effects over the scintillation estimation and the way to remove these errors**

In Eq. (1) the height of the ionospheric irregularity from the Earth's surface Z is a function of sec(θ). The zenith angle (θ) is a function of elevation angle (E) and can be expressed as

$$
\boldsymbol{\Theta} = \mathbf{\mathcal{O}} \mathbf{0} - \mathbf{E} \tag{3}
$$

Using the relation between satellite and zenith angle, Eq. (2) can be simplified as

$$\mathbf{S}\_4 \sim \left[ \sec \left( \mathbf{90} - \mathbf{E} \right) \sec \left( \mathbf{90} - \mathbf{E} \right)^{\mathbf{0} - 1/2} \right]^{1/2} \tag{4}$$

As we mentioned earlier, υ is a three-dimensional ionospheric irregularity spectral index [9]. One-dimensional spectral index (p) is related to the threedimensional spectral index as p = 2υ�1. If we simplify Eqs. (3) and (4), we will get to a direct dependence relationship between scintillation indices and zenith angle. Following Priyadarshi and Wernik [13], we can derive the spectral index p by using the log-log relationship of the scintillation index observation and cosecant of the satellite elevation angle [13]:

$$\mathbf{S}\_4 \sim \text{csc}(E)^{(p+2)/4} \text{ F}(\mathbf{a}, \mathbf{b}) \tag{5}$$

From Eq. (5) it is clear that the scintillation index is a power-law function of cosecant of the elevation angle with the power one-dimensional ionospheric irregularity spectral index (p) [13]. In order to simplify it more and avoid the dependence on the filter factor F(a,b), which is a complicated function of the ionospheric irregularity elongation parameters and which makes the overall ionospheric irregularity orientation dependence very complicated [13], we have considered the ionospheric radio-wave propagation environment as isotropic [9], and this turns F(a, b) = 1. Now if we plot log-log maps for S4 and Sin (E) angle, we can calculate the one-dimensional spectra index (p) from this relationship. Once we have spectral index, we can correct the scintillation for the geometry of propagation between the receiver and the transmitter using the Eq. (6):

S4\_corrected ¼ S4\_observed*=*csc Eð Þð Þ Pþ2 *=*4 (6)

**Figure 1** shows the non-corrected (S4\_observed) Vs-corrected scintillation indices (S4\_corrected) observed from the GPS scintillation receiver GSV 4004b deployed at

factor and is a function of ionospheric irregularity elongation parameters F(a,b), "a" is the elongation parameter of the irregularities along the filed lines and "b" is used for elongation across the geomagnetic field lines; υ is the three-dimensional

**Ionospheric irregularity form**

2 a:a (i.e., a = b) Sheets elongated both along the magnetic field and in transverse plane coinciding with local L shell

4 a:b and a < b This combination is impossible, as ionospheric structures cannot

have their spread more in transverse direction of the geomagnetic

are the distance to the source; *ℊ* is the common geometry and propagation factor, which is also a function of elongation parameters a and b; and <*δφ*2> is the phase variance in the satellite signal after passing through the ionospheric irregularity. Following the assumption of the theory of wave propagation in random medium, it is safe to assume at the signal frequency of interest that only the phase of the signal wave gets distorted [2] as the signal passes through the ionospheric irregularity of slab thickness L, and GPS scintillation receivers can observe the time series of the phase-modulated signal on the ground. Formulas (1) and (2) can be used to simulate the amplitude and phase scintillation. Study of the power spectrum of the ionospheric data improves the estimation of the local ionospheric irregularity form and their orientation with respect to the local geomagnetic field. Several ionospheric parameters such us spectral index, turbulence strength parameter, and phase fluctuations are essential for correcting the data contaminated through the

Following Eq. (2) discussed in Rino [9], scintillation index is a function of Fresnel filter factor F(a,b) which is a function of elongation parameters "a" and "b." A detailed explanation of this function is discussed in Rino [9]; as it is beyond the scope of this book chapter therefore we are not discussing it in more details. But, for the reader's convenience, we are providing a summary table (please see **Table 1**), which summarizes the different combinations of "a" and "b" giving rise to different

Scintillation modeling provides a general scenario of the ionospheric scintillations' global morphology and occurrence during different solar activity and space weather conditions. It is always not possible to obtain ionospheric scintillation observation during some space weather events, and during such situations, a realistic ionospheric scintillation model can be used to fill the data gaps. On the other hand, data assimilation techniques also use scintillation model to assimilate scintillation observation into the scintillation model in order to improve the forecast. There are two aspects that influence the occurrence and strength of the ionospheric scintillation. First is the geometrical effect between the radio-wave-emitting satellite and the receiver which can be at any different location, e.g., at the ground;

4*π* ; ZR = ZZs/(Z + Zs) and Zs

spectral index; q0 is the inner scale constant and Z ➔*λZRSecθ*

field

geometrical errors.

**94**

**S. No. Elongation**

**Table 1.**

**parameters' axial ratio**

1 a:1 (i.e., b = 1) Field aligned rods

*Satellites Missions and Technologies for Geosciences*

3 a:b and a > b Like wings

*Form of the ionospheric irregularities.*

ionospheric irregularity shapes.

**3. Scintillation modeling needs and discussions**

the Hornsund, Svalbard (76.9718° N, 15.7844° E). The red dots show the amplitude scintillation index, whereas the black dots show the phase scintillation index. If we compare these two figures, the gap between amplitude and phase scintillation index is very less in uncorrected case (on the left). We see that the number of amplitude and phase scintillation observations is reduced in the corrected case (on the right). It is evident from **Figure 1** that after correcting the scintillation data, we come over the geometrical effect for the amplitude as well as phase scintillation. After the geometrical effect correction, we observe two main things. Firstly, there is a reduction in the numerical peak value of the scintillation indices, and secondly, we do see the significant numerical level gap between amplitude and phase scintillation index data after the geometrical correction.

Here we see the scintillation index maximizes between 15 and 20° elevation angles as well as between 70 and 85° elevation angles. At 15–20° elevation angle, the multipath effects are dominant due to which we observe high-value scintillations. On the other hand, between 70 and 85° elevation, the angle orientation of the geomagnetic field line at Hornsund is such that it forms rodlike structure along the geomagnetic field lines. At certain combination of the elevation and azimuth angle, the receiver looks along the geomagnetic field lines. Due to such ionospheric irregularity structure orientation, GPS/GNSS signal travels more distance through the ionospheric irregularity; consequently, we observe the high numerical value of the

To demonstrate the simultaneous impact of the ionospheric irregularity structure and its orientation with respect to the local geomagnetic field lines, we have simulated amplitude scintillation index for a mid-latitude regions Weihai (geographic latitude 37.53°, geographic longitude 122.05°). We have simulated a midlatitude region for simulating the scintillation index (please see **Figure 3**) using the method discussed in Priyadarshi and Wernik [13] because at the mid-latitude orientation of the geomagnetic field line is neither completely horizontal (alike the

Such slant orientation of the geomagnetic field with respect to the local Earth's surface allows the ionospheric irregularities to evolve and settle in several forms. The orientation parameters along and across the geomagnetic field lines are shown in **Figure 3a** and **b**. The top-left panel shows the rodlike structure, in which we see that for lower elevation angle (≤10°), the scintillation index is very high. As the elevation angle gradually increases, there is a reduction in the scintillation index, and the scintillation index is minimal for higher elevation angle (≥70°). It means that when the spread of the ionospheric irregularity is not significant neither along

a = 1; b=1 a = 1; b=10

a = 10; b=1 a = 10; b=10

*Simulation scintillation indices for the different combinations of the ionospheric irregularity elongation parameters: rodlike (top-left), winglike (top-right and bottom-left), and sheetlike (bottom-right).*

**Figure 3.**

**97**

scintillation indices at this elevation angle range.

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

equatorial region) nor completely vertical (as at the polar region).

**Figure 2** shows the normalized simulated scintillation index map (scintillation index divided by the scintillation index at 25° elevation angle). This map shows the scintillation index simulation for a high-latitude station in Hornsund, Svalbard.

#### **Figure 1.**

*Amplitude (in orange) and phase scintillation (in black) index observations for Hornsund, Svalbard (76.9718° N, 15.7844° E), (on left) without geometrical effect correction, (on right) with geometrical effect correction.*

#### **Figure 2**.

*Normalized simulated amplitude scintillation index for Hornsund, Svalbard, vs elevation angle of the transmitter.*

#### *Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

the Hornsund, Svalbard (76.9718° N, 15.7844° E). The red dots show the amplitude scintillation index, whereas the black dots show the phase scintillation index. If we compare these two figures, the gap between amplitude and phase scintillation index is very less in uncorrected case (on the left). We see that the number of amplitude and phase scintillation observations is reduced in the corrected case (on the right). It is evident from **Figure 1** that after correcting the scintillation data, we come over the geometrical effect for the amplitude as well as phase scintillation. After the geometrical effect correction, we observe two main things. Firstly, there is a reduction in the numerical peak value of the scintillation indices, and secondly, we do see the significant numerical level gap between amplitude and phase

**Figure 2** shows the normalized simulated scintillation index map (scintillation index divided by the scintillation index at 25° elevation angle). This map shows the scintillation index simulation for a high-latitude station in Hornsund, Svalbard.

*Amplitude (in orange) and phase scintillation (in black) index observations for Hornsund, Svalbard (76.9718° N, 15.7844° E), (on left) without geometrical effect correction, (on right) with geometrical effect*

*Normalized simulated amplitude scintillation index for Hornsund, Svalbard, vs elevation angle of the*

scintillation index data after the geometrical correction.

*Satellites Missions and Technologies for Geosciences*

**Figure 1.**

*correction.*

**Figure 2**.

*transmitter.*

**96**

Here we see the scintillation index maximizes between 15 and 20° elevation angles as well as between 70 and 85° elevation angles. At 15–20° elevation angle, the multipath effects are dominant due to which we observe high-value scintillations. On the other hand, between 70 and 85° elevation, the angle orientation of the geomagnetic field line at Hornsund is such that it forms rodlike structure along the geomagnetic field lines. At certain combination of the elevation and azimuth angle, the receiver looks along the geomagnetic field lines. Due to such ionospheric irregularity structure orientation, GPS/GNSS signal travels more distance through the ionospheric irregularity; consequently, we observe the high numerical value of the scintillation indices at this elevation angle range.

To demonstrate the simultaneous impact of the ionospheric irregularity structure and its orientation with respect to the local geomagnetic field lines, we have simulated amplitude scintillation index for a mid-latitude regions Weihai (geographic latitude 37.53°, geographic longitude 122.05°). We have simulated a midlatitude region for simulating the scintillation index (please see **Figure 3**) using the method discussed in Priyadarshi and Wernik [13] because at the mid-latitude orientation of the geomagnetic field line is neither completely horizontal (alike the equatorial region) nor completely vertical (as at the polar region).

Such slant orientation of the geomagnetic field with respect to the local Earth's surface allows the ionospheric irregularities to evolve and settle in several forms. The orientation parameters along and across the geomagnetic field lines are shown in **Figure 3a** and **b**. The top-left panel shows the rodlike structure, in which we see that for lower elevation angle (≤10°), the scintillation index is very high. As the elevation angle gradually increases, there is a reduction in the scintillation index, and the scintillation index is minimal for higher elevation angle (≥70°). It means that when the spread of the ionospheric irregularity is not significant neither along

#### **Figure 3.**

*Simulation scintillation indices for the different combinations of the ionospheric irregularity elongation parameters: rodlike (top-left), winglike (top-right and bottom-left), and sheetlike (bottom-right).*

nor across the geomagnetic field lines, then the strength of the scintillation solely depends on the elevation angles. When the spread of the ionospheric structures are more either along (bottom-left) or across (top-right) the geomagnetic field lines, then the numerical value of the scintillation index depends on the combination of the elevation angle and azimuth and on the orientation of the irregularities with respect to the local geomagnetic field lines. As we can see that even for the winglike structures, the scintillation behavior is different for the irregularity spread along and across the geomagnetic field lines. For a = 1 and b = 10 (top-right figure), it shows the decrease in the scintillation with increasing elevation angle, and it also shows scintillation maximizes near two azimuth angles nearly 90° and 270°, respectively. At these two azimuth angles, the line of sight of the observer goes close to the vertical direction of the geomagnetic field lines; ionospheric irregularity structure orientations are vertical and in the direction of the geomagnetic field line. Due to such vertical irregularity orientation, we observe the sharp enhancement in the scintillation index. The third case (a = 10 and b = 1; bottom-left) seems quite similar to the case discussed in the figure at the top-left (a = 1 and b = 1), except 300° > azimuth<50°. In the fourth case (a = 10 and b = 10; bottom-right), there are two spikes at the azimuth 90° and 270°; these spikes are due to the direction of the geomagnetic field effect as well as a gradual decrease in the scintillation with increasing elevation angle. In summary, a certain combination of azimuth and elevation angle and orientation of the geomagnetic field allow radio-wave satellite signal passing more through the ionospheric irregularity structure.

#### **3.2 Limitations as well as efficacy in modeling the scintillation, due to solar activity, local seasons, local time, and geomagnetic activity**

It is very challenging to model ionospheric scintillation during different solar activity, season, local time, and geomagnetic activity conditions. The first limitation for empirical modeling may be due to the specific data unavailability during the particular geomagnetic, solar, and local seasons/time conditions. The modeler should be very careful in making the scintillation model sensitive to the several ionospheric anomalies that appear at different geographic locations and seasons. For example, winter anomaly causes more ionospheric scintillation production during the winter months than the summer months in mid-latitude regions. 20° of the magnetic equator is the equatorial anomaly region. In the equatorial anomaly region, we observe strong ionospheric scintillation as a lot of scintillation-producing ionospheric irregularity deposit in these regions due to the fountain effect. At the equatorial electrojet regions which are at 3° of the magnetic equator, we also observe severe ionospheric scintillations. Other events such as X-rays, sudden ionospheric disturbances (SID); protons, polar cap absorption (PCA); and geomagnetic storms and lightning can also produce a significant amount of scintillationproducing ionospheric irregularities.

universal time hours (UT). As evident from **Figure 4** (between 60 and 70° MLAT), during a weak geomagnetic storm (30 > =Dst > = 50 nT) that occurred on 03 January 2014, the amplitude scintillation index shows quite similar fluctuations with the phase scintillation index (please see 16–20 MLT at 60–70° S CGMLAT; 0–6 MLT at 60–70° S CGMLAT, and 10–14 MLT at 60–70° S CGMLAT). But, overall phase scintillation values were relatively higher than the amplitude scintillation index. However, during a strong geomagnetic storm (Dst < = 100 nT) that occurred on 27 February 2014, we see that some part of the amplitude scintillation index shows resemblance with the phase scintillation index map, for instance, 0–2 MLT and 16–18 MLT at 60–70° CGMLAT, but, in the rest of the part near the dusk regions at all the CGMLATs 60–90° S CGMLAT, phase scintillation indices are much higher and high in occurrence than the amplitude scintillation index. It should be noted here that it is not compulsory that S4 and σφ have similar character of variations. In general it depends on the scale of the ionospheric turbulences. In case of kilometers size, the refractive scintillations of the phase are predominant, but amplitude scintillations are minimal. In case of hundred metersized turbulence, both refractive and diffractive mechanisms are present, and, hence S4 and σφ indices have high similarity of variations (please see [19] for

*Modeled amplitude and phase scintillation index over Antarctica during a moderate geomagnetic storm that*

Space physicist generally explains this that during such strong geomagnetic storms, large-scale ionospheric irregularity structures often enter from the cusp region, and following the convection cells, they pass through the deep inside the polar cap and exit near the magnetic midnight or dusk sector of the polar region. This explanation seems true, but, following the scintillation theory described in Wernik et al. [1], when phase scintillation index keeps on increasing but amplitude

details).

**99**

**Figure 4.**

*occurred on 03 January 2014.*

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

On the other hand, at the polar latitudes, it is widely believed that the phase scintillation index is more sensitive to the solar/geomagnetic events than the amplitude scintillation index [14–17]. Let us understand this by an illustrative example. Following the South Pole scintillation model developed by Priyadarshi et al. [18], we have produced modeled amplitude and phase scintillation maps for two geomagnetic storms, which occurred in the year 2014 (please see **Figures 4** and **5**). This South Pole empirical scintillation model uses two b-spline functions of degree 4, along with the Ap index and scintillation observation recorded over South Pole GSV4004 scintillation receiver (location, 89.99° geographic latitude; 93.77° geographic longitude; geomagnetic coordinate, 73.5°, 127.8°). Since the model uses a single GPS receiver data, therefore, MLT time lags by 4 hours and 22 minutes to the *Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

**Figure 4.**

nor across the geomagnetic field lines, then the strength of the scintillation solely depends on the elevation angles. When the spread of the ionospheric structures are more either along (bottom-left) or across (top-right) the geomagnetic field lines, then the numerical value of the scintillation index depends on the combination of the elevation angle and azimuth and on the orientation of the irregularities with respect to the local geomagnetic field lines. As we can see that even for the winglike structures, the scintillation behavior is different for the irregularity spread along and across the geomagnetic field lines. For a = 1 and b = 10 (top-right figure), it shows the decrease in the scintillation with increasing elevation angle, and it also shows scintillation maximizes near two azimuth angles nearly 90° and 270°, respectively. At these two azimuth angles, the line of sight of the observer goes close to the vertical direction of the geomagnetic field lines; ionospheric irregularity structure orientations are vertical and in the direction of the geomagnetic field line. Due to such vertical irregularity orientation, we observe the sharp enhancement in the scintillation index. The third case (a = 10 and b = 1; bottom-left) seems quite similar to the case discussed in the figure at the top-left (a = 1 and b = 1), except 300° > azimuth<50°. In the fourth case (a = 10 and b = 10; bottom-right), there are two spikes at the azimuth 90° and 270°; these spikes are due to the direction of the geomagnetic field effect as well as a gradual decrease in the scintillation with increasing elevation angle. In summary, a certain combination of azimuth and elevation angle and orientation of the geomagnetic field allow radio-wave satellite

*Satellites Missions and Technologies for Geosciences*

signal passing more through the ionospheric irregularity structure.

**activity, local seasons, local time, and geomagnetic activity**

storms and lightning can also produce a significant amount of scintillation-

On the other hand, at the polar latitudes, it is widely believed that the phase scintillation index is more sensitive to the solar/geomagnetic events than the amplitude scintillation index [14–17]. Let us understand this by an illustrative example. Following the South Pole scintillation model developed by Priyadarshi et al. [18], we have produced modeled amplitude and phase scintillation maps for two geomagnetic storms, which occurred in the year 2014 (please see **Figures 4** and **5**). This South Pole empirical scintillation model uses two b-spline functions of degree 4, along with the Ap index and scintillation observation recorded over South Pole GSV4004 scintillation receiver (location, 89.99° geographic latitude; 93.77° geographic longitude; geomagnetic coordinate, 73.5°, 127.8°). Since the model uses a single GPS receiver data, therefore, MLT time lags by 4 hours and 22 minutes to the

producing ionospheric irregularities.

**98**

**3.2 Limitations as well as efficacy in modeling the scintillation, due to solar**

It is very challenging to model ionospheric scintillation during different solar activity, season, local time, and geomagnetic activity conditions. The first limitation for empirical modeling may be due to the specific data unavailability during the particular geomagnetic, solar, and local seasons/time conditions. The modeler should be very careful in making the scintillation model sensitive to the several ionospheric anomalies that appear at different geographic locations and seasons. For example, winter anomaly causes more ionospheric scintillation production during the winter months than the summer months in mid-latitude regions. 20° of the magnetic equator is the equatorial anomaly region. In the equatorial anomaly region, we observe strong ionospheric scintillation as a lot of scintillation-producing ionospheric irregularity deposit in these regions due to the fountain effect. At the equatorial electrojet regions which are at 3° of the magnetic equator, we also observe severe ionospheric scintillations. Other events such as X-rays, sudden ionospheric disturbances (SID); protons, polar cap absorption (PCA); and geomagnetic

*Modeled amplitude and phase scintillation index over Antarctica during a moderate geomagnetic storm that occurred on 03 January 2014.*

universal time hours (UT). As evident from **Figure 4** (between 60 and 70° MLAT), during a weak geomagnetic storm (30 > =Dst > = 50 nT) that occurred on 03 January 2014, the amplitude scintillation index shows quite similar fluctuations with the phase scintillation index (please see 16–20 MLT at 60–70° S CGMLAT; 0–6 MLT at 60–70° S CGMLAT, and 10–14 MLT at 60–70° S CGMLAT). But, overall phase scintillation values were relatively higher than the amplitude scintillation index. However, during a strong geomagnetic storm (Dst < = 100 nT) that occurred on 27 February 2014, we see that some part of the amplitude scintillation index shows resemblance with the phase scintillation index map, for instance, 0–2 MLT and 16–18 MLT at 60–70° CGMLAT, but, in the rest of the part near the dusk regions at all the CGMLATs 60–90° S CGMLAT, phase scintillation indices are much higher and high in occurrence than the amplitude scintillation index. It should be noted here that it is not compulsory that S4 and σφ have similar character of variations. In general it depends on the scale of the ionospheric turbulences. In case of kilometers size, the refractive scintillations of the phase are predominant, but amplitude scintillations are minimal. In case of hundred metersized turbulence, both refractive and diffractive mechanisms are present, and, hence S4 and σφ indices have high similarity of variations (please see [19] for details).

Space physicist generally explains this that during such strong geomagnetic storms, large-scale ionospheric irregularity structures often enter from the cusp region, and following the convection cells, they pass through the deep inside the polar cap and exit near the magnetic midnight or dusk sector of the polar region. This explanation seems true, but, following the scintillation theory described in Wernik et al. [1], when phase scintillation index keeps on increasing but amplitude

ionospheric scintillation. If taken care well, the model limitations caused due to geometrical effects such as multipath, elevation angle dependence, and form of ionospheric irregularities can be reduced, and the modeled results would provide an error-free estimation of the scintillation indices. Scintillation observations are one of the scintillation model input. By studying the log-log variation of the scintillation index, we can derive the scintillation index correction parameters as discussed in Section 2 [13]. These scintillation correction parameters are used to correct the scintillation model input data. We have demonstrated the geometric corrections between the satellite and receivers (see **Figure 1**) and its importance to use corrected scintillation indices as model input for modeling the ionospheric scintillation indices. Ionospheric scintillation highly depends on the orientation as well as the spread of the ionospheric irregularities with respect to the local geomagnetic field lines. In order to get the real and justified model's output, we must use the input scintillation data in our model for all available, local seasons, local time, and solar/geomagnetic activity duration. At certain elevation angles, scintillation indices show unusual enhancement (please see **Figure 2**); it is because the signal travels long distances through the ionospheric irregularity structures at the lower elevation angle, and at certain elevation angle, the receiver look along the vertical orientation of the ionospheric irregularities with respect to the local geomagnetic field line. The orientation of the ionospheric irregularities structures influences the ionospheric scintillation intensity. We have compared the four types of combination of ionospheric irregularity structures using four different combinations of elongation axial ratios "a" and "b" (please see **Figure 3** and its related discussion). **Figure 3** demonstrated that at a few combinations of azimuth and elevation angles, the orientation of the geomagnetic field allows radio-wave satellite signal passing more through the ionospheric irregularity structure. Apparently, scintillation intensity enhances at these locations. Through two modeled South Pole scintillation maps during the moderate and strong geomagnetic storms (case studies related to **Figures 4** and **5**), we have demonstrated that the adoption of the scintillation model provides its high case sensitive to the latitudinal anomalies. For example, winter anomaly which occurs at the mid-latitude ionosphere that causes more scintillation occurrence in winter months as compared to the summer months enhanced scintillation 20° to either side of the geomagnetic equator and EEJ effect which occurs 3° on either side of the geomagnetic equator. For high-latitude scintillation modeling, it is essential to consider the ionospheric ionization difference during the sunlit months and dark months. The importance of optimizing the numerical scale of phase and amplitude scintillation indices at the polar latitudes is also discussed. In summary, the presented book chapter discusses all the factors that significantly influence the ionospheric scintillation and possible methods to minimize the estimation errors that caused them. Physics-based models are good to produce the global morphology of the ionospheric scintillation, but, they often fail to produce the exact scintillation index during active solar events. Therefore, empirical models are better as they use the physics-based model as background, but they keep on using the real observations as the model input. These joint efforts work in the derivation and development of a decent ionospheric scintillation model, which can produce equivalent scintillation indices for all the geographic latitudes, local weather, local time, and solar/

*Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*

geomagnetic activity conditions.

The scintillation data used in this book chapter has been thankfully obtained

from the Polish Polar Station Hornsund, Svalbard. We also thank the Space Research Centre, Polish Academy of Sciences (SRC-PAS) for requesting this data.

**Acknowledgements**

**101**

**Figure 5.**

*Modeled amplitude and phase scintillation index over Antarctica during a strong geomagnetic storm that occurred on 27 February 2014.*

scintillation seizes to increase, then at this instance, the ionospheric irregularity plasma waves are not more coherent, and these fluctuations cannot be considered as real scintillation due to lack of interference between two noncoherent plasma waves at high-phase fluctuations [1]. For this situation the modeler must optimize the numerical scales of the observed scintillation indices such that the amplitude and phase scintillation indices show similar fluctuation to each other. Priyadarshi et al. [20] used an optimized numerical scale for the amplitude and phase scintillation indices observed during a geomagnetic storm that occurred on 27 February 2014. Ionospheric scintillation index optimization is a way in which by using different amplitude and phase scintillation variation scale it helps us see the same trend variation in the amplitude/phase scintillation indices. In the event discussed in Priyadarshi et al. [20], phase scintillation index variations were optimized between 0.05 and 0.5, and amplitude scintillation index variations were optimized between 0.05 and 0.2. The dayside cusp region amplitude and phase scintillation indices gave similar information at different numerical scales. This study also demonstrated that the amplitude scintillation index is also a useful scintillation index if the proper numerical scale is chosen. Large-scale ionospheric irregularities such as storm-enhanced density (SED) and tong of ionization (TOI) were not found necessarily producing ionospheric scintillation [20].

#### **4. Summary**

In general it is more typical when the carrier-phase loss of lock happens due to the sharp signal-to-noise ratio fading (please look [21, 22] for more details). In this book chapter, we have discussed some peculiar modeling tricks and tips of

#### *Ionospheric Scintillation Modeling Needs and Tricks DOI: http://dx.doi.org/10.5772/intechopen.88313*