| 改进粒子滤波算法及其应用仿真 |
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| 引用本文： | 张军,所玉君,董小丰,张玉朋.改进粒子滤波算法及其应用仿真[J].计算机系统应用,2013,22(12):104-107. |
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| 作者姓名： | 张军 所玉君 董小丰 张玉朋 |
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| 作者单位： | 中国航天科工集团 第八三五七研究所, 天津 300308;中国航天科工集团 第八三五七研究所, 天津 300308;空军驻天津地区军事代表室, 天津 300308;河北工业大学 控制学院, 天津 300130 |
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| 摘 要： | 针对目标跟踪中粒子滤波算法的估计精度不高、粒子退化问题，文中提出了一种GH．RPF算法．在粒子滤波的基础上，应用高斯．厄米特滤波来产生重要密度函数，同时对重采样采用正则变换以改善采样粒子的多样’生．将该算法应用于非线性、非高斯的目标跟踪中，仿真结果表明，与标准粒子滤波及EKPF相比，该算法的滤波精度更高，具有更高的跟踪性能．
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| 关 键 词： | 粒子退化 粒子滤波 正则变换 跟踪 |
| 收稿时间： | 5/5/2013 12:00:00 AM |
| 修稿时间： | 6/7/2013 12:00:00 AM |
Improved Particle Filter Algorithm and Application Simulation |
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| ZHANG Jun,SUO Yu-Jun,DONG Xiao-Feng and ZHANG Yu-Peng.Improved Particle Filter Algorithm and Application Simulation[J].Computer Systems& Applications,2013,22(12):104-107. |
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| Authors: | ZHANG Jun SUO Yu-Jun DONG Xiao-Feng and ZHANG Yu-Peng |
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| Affiliation: | The 8357th Research Institute of China Aerospace Science and Industry Corp, Tianjin 300308, China;The 8357th Research Institute of China Aerospace Science and Industry Corp, Tianjin 300308, China;Military Delegation Office for Tianjin Region of PLA's Airforce, Tianjin 300308, China;School of Control Science and Engineering, Hebei University of Technology, Tianjin 300130, China |
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| Abstract: | In view of the low precision of particle filter algorithm and particle degradation in target tracking, a GH-RPF algorithm is put forward. Based on particle filter, Gauss-Hermite filter is applied to generate the importance density function, and meanwhile canonical transformation is adopted to re-sampling in order to improve the diversity of particles. If the algorithm is applied to nonlinear and non-Gaussian target tracking, it can be seen from the simulation result that the filtering accuracy is higher and tracking performance is better compared to the standard particle filter algorithm as well as EKPF. |
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| Keywords: | particle degradation particle filter canonical transformation tracking |
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