Abstract
In this paper, we present a comparative study of several nonlinear filters, namely, extended Kalman Filter (EKF), unscented KF (UKF), particle filter (PF), and recursive linear minimum mean square error (LMMSE) filter for the problem of satellite trajectory estimation. We evaluate the tracking accuracy of the above filtering algorithms and obtain the posterior Cramer-Rao lower bound (PCRLB) of the tracking error for performance comparison. Based on the simulation results, we provide recommendations on the practical tracking filter selection and guidelines for the design of observer configurations.
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