A pseudo linear Kalman filtering algorithm for bearings-only maneuvering target tracking

Abstract

A modified range parameterized instrumental variable pseudo linear Kalman filter (MRP-IVPLKF) algorithm is proposed for single station bearings-only ground maneuvering target tracking. Firstly, based on 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 instrumental variable pseudo linear Kalman filters are independently operated. Then, based on the filtering innovation and innovation covariance, the sub-filter weights are updated and target maneuvering is detected, ensuring filter stability by resetting the sub-filter weights and state information. Finally, the state information of each sub-filter is weighted and fused to obtain the target state, solving the problem of the decrease in tracking accuracy caused by unknown initial range and target maneuvering. The simulation results show that the position tracking accuracy of the algorithm proposed in this article is significantly improved compared to traditional methods, and can effectively achieve tracking of maneuvering targets.