Research on ship tracking based on adaptive particle filter

Locating remote slow sea-surface targets with airborne radar is a problem of the non-linear and non-Gaussian state estimation, resulting in the deviation of the target location and the track jitter when dealing with tradition Kalman filter. In this paper, adaptive particle filter (APF) is used to solve the ship tracking problem under glint noise. The algorithm can choose the number of particles based on KLD-Sampling, which is efficient and has smaller time consumption. Computer simulation proves that adaptive particle filter can track quickly sea-surface targets under glint noise, and the tracking performance is superior to that of standard particle filter (PF), so APF is practically valuable for engineering use.