an array of magnetic sensors and a digital signal processor are used to break a target magnetic dipole field into its components , and a magnetic signature of the present magnetic field is created . predicted target signatures are precomputed for multiple magnetic orientations of the dipole at each of a plurality of range locations , expressed in terms of anderson functions , which are a set of equations that decompose the magnetic field in each of the magnetic response locations , and are stored in a lookup table for reference . input data measured by the sensors are processed and each sensor &# 39 ; s magnetic value is predicted to process against background noise using the other sensors of the array . a long term time average consistent with the relative motion of the target is computed using bandpass filtering of the signals from the sensor array . the bandpass filtered data is used to update the predicted data so that anomalies and other non - target data is removed from the signals that are processed . the data are then expressed in terms of anderson functions . the data are matched filtered , wherein it is correlated with the stored precomputed predicted target signatures . the correlation yields a set of values that is then thresholded . if a target is present at any of the locations , then the correlated normalized value computed as stated above will be higher than the chosen threshold . the target locations that are above the threshold are then displayed on a monitor showing the relative location and dipole of orientation .