A Bearings-only Tracking Algorithm based on Multiple Model Filtering

In the bearings-only passive locating system with single station,the Extended Kalman Filtering(EKF) algorithm is used to diverging when the initial state estimation of the target is of low precision.In this paper,a multiple-model EKF algorithm is presented to solve this problem.According to the initial state estimation,five EKF models are designed to estimate the motion state of the target.When the multiple-model EKF process comes to steady-state, the single-model filtering algorithm is applied.Simulation results indicate that the proposed algorithm is valid.