Bearing-Only Target Tracking Based on Piecewise Backward Smoothing Kalman Filter

Abstract

In order to solve the problem that the Unscented Kalman Filter algorithm is sensitive to the initial value selection and the noise is easy to expand the error in the recursive process, a piecewise backward smoothing Kalman filter method is proposed in this paper. To reduce the influence of noise, the observation data is optimized in sections, and the forward and reverse use of historical data is increased. The simulation results under different initial distance error, different observation angle variance and different initial velocity error show that the proposed method is effective in underwater bearings only target tracking, and the effect of Unscented Kalman filter is obviously improved, the estimation error is greatly reduced, and the estimation accuracy and stability are improved.