Bearing-only tracking using range-parameterized shifted Rayleigh filter

In this paper, we modified the shifted Rayleigh filter (SRF) to improve its performance of tracking with bearing-only measurement. The proposed method uses multiple parallel SRF with different initial positions and it is named as range parameterized shifted Rayleigh filter (RP-SRF). The RP-SRF is applied to an underwater target motion analysis (TMA) where the target moves in a nearly straight line motion with constant velocity, and the observer maneuvers to track the target. The performance of the proposed estimator is compared with the SRF, cubature Kalman filter (CKF), and RP-CKF in terms of root mean square error (RMSE), percentage of track loss, and computational time. Simulation results indicate that the RP-SRF is more accurate than the CKF, SRF, and RP-CKF and would be ahead of its nearest competitor for underwater bearing-only tracking.

Automated summary

In this paper, the shifted Rayleigh filter (SRF) is modified to improve its tracking performance in bearing-only measurement. The proposed range parameterized shifted Rayleigh filter (RP-SRF) is applied to underwater target motion analysis (TMA) and compared with other filters. The simulation results show that RP-SRF outperforms its competitors in terms of accuracy for underwater bearing-only tracking.