非线性滤波算法在机动目标跟踪中的研究

Performance comparisons of nonlinear filtering algorithms for maneuvering target tracking

介绍了3种最基本非线性滤波算法——扩展卡尔曼滤波(EKF)、无迹卡尔曼滤波(UKF)和粒子滤波(PF)算法的理论在机动目标跟踪中的应用。通过仿真试验对三者性能进行了分析比较。

Maneuvering target tracking is a nonlinear problem that involves the estimation of the state at every time instant. This paper gives a brief introduction of three basic nonlinear filtering algorithms, such as EKF, UKF and PF. The comparison of the three algorithms＇ performance in targettracking is presented and the simulation results are also given.