Particle Filter for Underwater Bearings-Only Passive Target Tracking

Abstract

Passive target tracking is in essence the problem of nonlinear filtering, where the system dynamics equations are usually linear while the measurement equations are nonlinear, and the aim is to obtain the target's state based on the nonlinear measurements. Particle filter is an effective nonlinear filtering algorithm in nonlinear and non-Gaussian state space. According to the characteristics of underwater bearings-only passive target tracking, the particle filter algorithm used in nonlinear problems of underwater bearings-only passive target tracking has been proposed in this paper. The proposed algorithm can overcome the shortcomings of easy divergence, low tracking accuracy and large error in conventional linearized methods such as EKF and UKF. Computer simulation results demonstrate that the particle filter has enhanced the stability of the filtering, and has better tracking accuracy than EKF and UKF algorithm. It has received good results.