Bearings-Only Maneuvering Target Tracking Based on Modified Range Parameterized - Bias Compensation Pseudo Linear Kalman Filter Algorithm

A modified range parameterized bias compensation pseudo linear Kalman filter (MRP-BCPLKF) algorithm is proposed for single station bearings-only ground maneuvering target tracking. Firstly, according to the detection range of the observation station, the relative range between the target and the observation station is divided into several sub-intervals using range parameterization, and bias compensation pseudolinear filters are independently operated. Then, the sub-filter weights are updated and target maneuvering is detected by using the filtering innovation and innovation covariance. Each sub-filter’s stability is ensured by resetting weights and state information. Finally, the state information of each sub-filter is weighted and fused to obtain the target state. The simulation results show that the proposed algorithm can effectively track maneuvering target and reduce the impact of unknown initial range on tracking accuracy. The position tracking accuracy of the proposed algorithm has been improved by 13% and 11% compared to extended Kalman filter and cubature Kalman filter, respectively.