Research on bearing-only target tracking of UUV under underwater strong noise disturbance

Abstract

Aiming at the problem of bearing-only target tracking (BOTT) for UUVs in complex and dynamic ocean environments, the system is susceptible to interference from strong noise. This interference can lead to large noise covariance, poor tracking accuracy, and even filter divergence. An algorithm based on robust adaptive cubature Kalman filter (RACKF) is proposed. The algorithm consists of a noise statistics estimator (NSE) and a cubature Kalman filter (CKF). To ensure the robustness of the NSE, the paper builds a fault-tolerant NSE consisting of an unbiased NSE and a biased NSE. The simulation results show that the algorithm improves the filtering accuracy and robustness under the condition of underwater strong noise disturbance, which proves the effectiveness of the algorithm proposed in this paper.