基于改进粒子滤波的静电目标跟踪算法  

Electrostatic Target Tracking Algorithm Based on Improved Particle Filter

作　　者：李耀明[1] 付巍[2] 

机构地区：[1]中北大学机械工程与自动化学院,山西太原030051 [2]中国航空工业集团公司北京长城测试计量技术研究所,北京100095

出　　处：《探测与控制学报》2010年第2期64-67,72,共5页Journal of Detection & Control

基　　金：山西省青年自然科学基金项目资助(2009021022-2)

摘　　要：针对静电探测的数学模型结构复杂、强非线性以及实验测量数据存在极大不确定性的特点和传统粒子滤波(PF)算法存在的缺陷,提出了一种改进的粒子滤波(UPF)算法。该算法以无迹卡尔曼滤波(UKF)算法生成替代分布并从中采样,理论分析与仿真结果均表明,UPF算法能够提高静电探测系统目标跟踪的稳定性和精确性,解决了传统PF算法中以转换先验密度函数作为替代分布所引发的各种问题,具有较高的实用价值和广泛的应用前景。Against the complexity and nonlinear of Electrostatic target tracking, uncertainty of the experimental data and the shortcomings of the traditional particle filter （PF）, an improved particle filter algorithm called un- scented particle filter （UPF） is proposed. This algorithm generates a proposal distribution by unscented Kalman filter （UKF） method and draws samples from it, the theoretical analysis and simulation results demonstrate that the UPF algorithm improves stability and accuracy of tracking, and solves the various problems caused by PF which uses transition prior density function as the proposal distribution. The UPF has high practical value and broad application prospect.

关 键 词：静电探测 无迹粒子滤波 目标跟踪 

分 类 号：TN911.23[电子电信—通信与信息系统]