An Iterative Extended kalman filter algorithm applying Doppler and bearing measurements for underwater passive target tracking
Shasha Ma, Ning Sun · 2020
Based on bearing and Doppler frequency measurements, this paper presents a new method of state estimation for passive underwater target applying Extended Kaman filter (EKF). By linearizing the measurement equation through Jacobian, the state of passive underwater target is estimated with iterative algorithm. The Monte-Carlo simulation results show that the method can efficiently improve the accuracy of state estimation for passive underwater target. The performance of proposed algorithm for state estimation is better than that with bearing only observation applying EKF algorithm. Presented approach and obtained results may be useful in underwater passive target tracking and command decision-making application.