基于UKF算法的惟方位单站无源跟踪

Single Observer Bearings-Only Tracking Based on UKF

单站无源跟踪问题本质上是非线性估计问题,使用传统的EKF算法进行跟踪滤波,得到的结果误差较大,容易产生发散现象。本文在惟方位跟踪中应用UKF算法,仿真结果表明,与EKF相比,采用UKF算法跟踪精度较明显的提高,同时增强了滤波器的稳定性,有效地改善了跟踪性能。

Single observer Passive tracking, which is a non - linear parameter estimate issue in nature, used EKF algorithm in the past. But this brings large errors and easily leads to divergence. -In this paper, we introduce a new algorithm named Unscented Kalman Filter （UKF） and apply it in single observer bearing - only passive tracking system. Thus we solve the problems the EKF brings. The results of the simulation have shown us that using UKF leads to high precision, enhances stability and improves the performance of tracking effectively.