Modified iterated extended Kalman particle filter for single satellite passive tracking

Authors: Panlong Wu, JIANSHOU KONG, Yuming Bo

Abstract: Single satellite-to-satellite passive tracking techniques have great significance in space surveillance systems. A new passive modified iterated extended Kalman particle filter (MIEKPF) using bearings-only measurements in the Earth-Centered Inertial Coordinate System is proposed. The modified iterated extended Kalman filter (MIEKF), with a new maximum likelihood iteration termination criterion, is used to generate the proposal distribution of the MIEKPF. Moreover, a new measurement update equation of the MIEKF is derived by modifying the objective function of the Gauss--Newton iteration. The approximated second-order linearized state propagation equation, Jacobian matrix of state transfer, and measurement equations are derived in satellite 2-body movement. The tracking performances of the MIEKPF, iterated extended Kalman particle filter (IEKPF), extended Kalman particle filter (EKPF), and extended Kalman filter (EKF) are compared via Monte Carlo simulations through simulated data from STK8.1. The simulation results indicate that the proposed MIEKF is capable of passively tracking a low earth circular orbit satellite with a high earth orbit satellite using bearings-only measurements and has higher tracking precision than the traditional algorithms.

Keywords: Bearings, Gauss--Newton iteration, modified iterated extended Kalman filter, particle filter, passive tracking

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