Abstract:

Pseudo-linear estimation algorithm is one of the primary bearings-only target tracking algorithms. Although the algorithm could be implemented simply, it produces serious deviate estimates. A new instrumental variable method is presented to improve the bistatic localization performance. The value of object state obtained from last time is iterated once by Levenberg-Marquardt algorithm,  and the iterative value is used as an auxiliary variable to estimate the motion parameters by the weighted least-square method. Simulation results show that the proposed algorithm can achieve the Cramer-Rao low bound (CRLB) efficiently for Gaussian noise around small error regions compared with the extended Kalman filter and pseudolinear estimation algorithm.