On the Cramér–Rao lower bound for biased bearings-only maneuvering target tracking

This paper aims to investigate the theoretical performance of bearings-only maneuvering target tracking when fixed measurement biases exist. Firstly, the general formulation of Cramér–Rao lower bound (CRLB) is presented when both target's maneuver and fixed measurement biases work simultaneously in a bistatic system, and the corresponding recursive CRLB formulation is then derived. Finally, a maneuver detection method is developed to calculate the approximation of the theoretical CRLB. Numerical simulation results indicate either that the proposed or the fuzzy-neural-network-based maneuver detection method can yield a satisfying CRLB compared with the theoretical CRLB, but the proposed method is easier to implement owing to directly utilizing the target's bearing information.