In principle either approach allows one to estimate a quantity function (the state of a dynamical system) from noisy measurements, even when the system is non-linear (thus generalizing the earlier results of Wiener and Kalman for linear systems and solving a central problem in estimation theory).
Both methods can estimate a quantity function (the state of a dynamical system) from noisy measurements, even when dealing with non-linear systems (thus expanding on earlier results for linear systems and tackling a central challenge in estimation theory).