Abstract:

In order to improve the tracking accuracy of targets in reentry phase, a new distributed fusion algorithm is proposed by combining the square-root unscented Kalman filter (UKF) with the multi-sensor distributed fusion tracking algorithm. This algorithm uses the square-root UKF to calculate the state estimation values of local sensors respectively, and consequently the system fusion state estimation and covariance is obtained by applying the multi-sensor distributed fusion rules. At the same time, the state covariance is allocated to the local sensors. The simulation results show that the new algorithm has a higher tracking performance, and it is a very effective nonlinear fusion tracking algorithm.