Unscented Kalman filter with improved forward-backward prediction for target tracking
Yang Liu, Pingbo Wang · International Conference on Electronic Information Technology (EIT 2022) · 2022
In order to improve the accuracy of active sonar underwater target tracking, an improved algorithm is proposed based on the existing forward-backward prediction algorithm of unscented Kalman filter. The algorithm can adaptively perform forward-backward prediction operation, and replace the measured value with the state estimate value of the past moment to avoid nonlinear problem in reverse prediction. The simulation results show that when the total calculation amount is almost the same, the algorithm can improve the accuracy of state estimation better than the standard algorithm.