电子学报Issue(10)：1970-1976,7.DOI:10.3969/j.issn.0372-2112.2014.10.016
基于权重一致性优化的实时Marginalized粒子滤波算法
Real-Time Marginalized Particle Filter Based on Weights Consistency Optimization
摘要
Abstract
Aiming to adverse influence on the filtering precision of nonlinear state estimation caused by the random observa-tion noise and the improvement of larger calculated amount from linear state estimation in marginalized particle filter ,a novel real-time marginalized particle filter based on weights consistency optimization is proposed .Firstly ,according to the extraction and uti-lization of prior information from observation system model ,the consistency optimization method of particle weights in observation lifting scheme is given by the construction of consistency distance and consistency matrix ,which improves the filtering precision of particle filter used in nonlinear state estimation .Secondly ,the real-time marginalized particle filter is proposed by the structure opti-mization of time update and observation update steps ,which decrease the computational complexity of Kalman filter used in the lin-ear state estimation in view of Monte Carlo simulation principle .Finally ,the concrete steps of new algorithm are given by the dy-namic combination of the consistency optimization method and the real-time marginalized particle filter .The filtering precision and calculated amount of new algorithm is analyzed on the basis of single station radar observation target tracking simulation scene .The theoretical analysis and experimental results show the feasibility and efficiency of algorithm proposed .关键词
非线性估计/Marginalized粒子滤波/量测提升/权重优化Key words
nonlinear estimation/Marginalized particle filter/observation lifting/weights optimization分类
信息技术与安全科学引用本文复制引用
胡振涛,刘先省,金勇,侯彦东..基于权重一致性优化的实时Marginalized粒子滤波算法[J].电子学报,2014,(10):1970-1976,7.基金项目
国家自然科学基金（No ．61300214，No ．U1204611，No ．61374134）；河南省高校科技创新团队支持计划（No ．13IRTSTHN021）；河南省基础与前沿技术研究计划（No ．132300410148）；河南省教育厅科学技术研究重点项目（No ．13A413066）；河南省青年骨干教师资助计划 （）
