Bearing‐only underwater uncooperative target tracking for non‐Gaussian environment using fast particle filter

Abstract

Abstract Bearing‐only tracking of an underwater uncooperative target is essential to defend the sea territory. Considering the influences by uncertain underwater environment, the purpose of this work is to estimate 2‐D locations and velocities of an interested underwater target for non‐Gaussian environment. In this work, a fast particle filter (FPF) based on the traditional particle filter (PF) with novel jet transport (JT) technique is proposed to deal with this problem. Aiming to overcome the heavy computation burden of the traditional PF that limits most of its practical applications, the JT technique can dramatically reduce the computation time and complexity in the particle evolution process, which contributes huge computational complexities to the traditional PF. Then, the proposed FPF is tested through simulations in the 2‐D underwater uncooperative target tracking scenario. Finally, the Monte Carlo simulation results demonstrate that the proposed FPF can track the underwater uncooperative target with the similar accuracies as the traditional PF but only occupies less than 20% of the computational resources.

Keywords

• adaptive Kalman filters
• adaptive estimation
• particle filtering (numerical methods)
• sonar tracking
• tracking filters