[1]刘峰,宣士斌,刘香品.佳点集的QMC粒子滤波算法及其应用[J].智能系统学报,2014,9(04):461-467.[doi:10.3969/j.issn.1673-4785.201305079]
 LIU Feng,XUAN Shibin,LIU Xiangpin.Quasi-Monte Carlo particle filter algorithm based on the good point set and its application[J].CAAI Transactions on Intelligent Systems,2014,9(04):461-467.[doi:10.3969/j.issn.1673-4785.201305079]
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佳点集的QMC粒子滤波算法及其应用(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年04期
页码:
461-467
栏目:
出版日期:
2014-08-25

文章信息/Info

Title:
Quasi-Monte Carlo particle filter algorithm based on the good point set and its application
作者:
刘峰1 宣士斌2 刘香品1
1. 广西民族大学 信息科学与工程学院, 广西 南宁 530006;
2. 广西混杂计算与集成电路设计分析重点实验室, 广西 南宁 530006
Author(s):
LIU Feng1 XUAN Shibin2 LIU Xiangpin1
1. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China;
2. Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Nanning 530006, China
关键词:
目标跟踪粒子滤波拟蒙特卡洛佳点集遮挡
Keywords:
target trackingparticle filter algorithmquasi-Monte Carlogood point setocclusion
分类号:
TP391.9
DOI:
10.3969/j.issn.1673-4785.201305079
摘要:
针对粒子滤波中粒子匮乏及样本聚集问题, 提出一种基于佳点集的拟蒙特卡洛粒子滤波算法(GPS-QMCPF)。该算法利用数论中的佳点集理论和方法来构造出一种新的拟蒙特卡洛序列。由于佳点集序列与随机点列和标准的拟蒙特卡洛序列相比分布更均匀、偏差更小, 使得在滤波过程中状态估计的精度和收敛速度都得到提高, 同时还能增加粒子有效样本数和降低重采样次数。实验结果表明, 提出的算法在非线性系统状态估计精度要优于粒子滤波和标准的拟蒙特卡洛粒子滤波算法, 并且在视频目标跟踪的应用中, 针对跟踪目标受到遮挡的情况, 算法具有更高的跟踪精度, 同时跟踪的实时性也得到了一定程度的提高。
Abstract:
A quasi-Monte Carlo particle filtering algorithm based on the good point set (GPS-QMCPF) is proposed for solving the problem of particle shortage and sample aggregation. In the proposed algorithm, a new quasi-Monte Carlo sequence is constructed by using the good point set theory in the number theory. Considering that the good point set has a more homogeneous distribution and lower discrepancy than the standard QMC sequence and the random sequence, GPS-QMCPF can obtain a faster convergence speed in the filtering process and a better accuracy of the state estimation. Furthermore the re-sampling frequency is reduced, which results in a lower computational cost. Experimental results show that the proposed algorithm gets a more accurate estimation than the standard QMC filter and particle filter in the system state estimation, as well as with the video target tracking application. The proposed algorithm possesses the advantages of good tracking accuracy and a real-time standard, even in the case of occlusions.

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备注/Memo

备注/Memo:
收稿日期:2013-06-05。
基金项目:广西省自然科学基金资助项目(2012GXNSFAA053227)
通讯作者:宣士斌.E-mail:sbinxuan@gxun.cn
更新日期/Last Update: 1900-01-01