An improved UKF algorithm based on Rauch-Tung-Striebel smoother

In order to realize fast and stable passive location and tracking by a single non-moving observer, an improved Unscented Kalman Filter (UKF) algorithm based on Rauch-Tung-Striebel smoother (RTSS) is presented and an explicit analysis of its location performance is made. The proposed algorithm smoothes the previous state vector and covariance matrix by RTTS using the current filtering results, and then an initial value of higher precision is obtained. Simulation results indicate that the improved UKF algorithm can improve the location performance while keeping the real-time characteristic.