Target Tracking for Maneuvering Reentry Vehicles with Reduced Sigma Points Unscented Kalman filter

Abstract

Tracking a maneuvering reentry vehicles (MaRV) by processing radar measurements has attracted much attention of researchers. Compared with the traditional extended Kalman filter, the recently developed filtering algorithm called unscented Kalman filter are significant with its easy to tune, better accuracy and same order computational complexity. For the nine-dimension system in this paper a reduced points UKF combined reduced sigma points unscented transform (UT) with classical Kalman filter is presented to lessen computation burden. Simulation results show its effectiveness.