Underwater Bearings-Only Short Time Target Tracking Based on Initial Value Updating

Underwater passive bearings-only target tracking by single-observer has the advantages of simple layout and strong concealment. However, the filtering methods are sensitive to the initial value, and the actual engineering will encounter the situation of fast target speed, short observation time and less measurement data, which makes this problem significantly prominent. In view of this situation, this paper studies the causes and the effect of initial values on filtering, and presents an improved method of extended Kalman filter based on initial value update. By re-estimating and updating the initial values through backward iteration, the effect of the initial error on the filtering result is gradually reduced. The simulation results show that this method can reduce the dependence of the filter on initial value selection and the final estimation error.