太原理工大学学报2017，Vol.48Issue(1)：110-115,6.DOI:10.16355/j.cnki.issn1007-9432tyut.2017.01.018
基于差分进化改进粒子滤波的多径估计算法
An Improved Differential Evolution-Based Particle Filter for Multipath Estimation
摘要
Abstract
Multipath is the dominant error source for high‐accuracy positioning systems since it is uncorrelated and uncertain at different location and can not be eliminated by the differential technology .To this end ,it is significant for eliminating the multipath error and improving the positioning accuracy to estimate multipath parameters .In this paper ,the multipath estimation problem is transformed into a parameter estimation problem ,and the particle filter (PF ) algo‐rithm is applied for multipath estimation .However ,there is a drawback of particle impoverish‐ment in standard PF by using re‐sampling strategy ,w hich may lead to PF converging to a w rong value .In order to solve this problem ,a differential evolution (DE) algorithm instead of the re‐sampling strategy is used to generate new particles in PF .The proposed algorithm is named as improved differential evolution‐based particle filter (DEPF ) .In DEPF ,DE algorithm is used to promote the new particle moving towards the true post probability density distribution of the tar‐get state ,w hich can avoid particle impoverishment .Simulation results show that the DEPF algo‐rithm outperforms PF and EKF for multipath estimation in non‐Gaussian noise .关键词
状态估计/粒子滤波/差分进化/多径干扰/导航系统Key words
state estimation/particle filter/differential evolution/multipath interference/navi-gation system分类
信息技术与安全科学引用本文复制引用
邢艳君,程兰,任密蜂,王志远,谢刚..基于差分进化改进粒子滤波的多径估计算法[J].太原理工大学学报,2017,48(1):110-115,6.基金项目
国家自然科学基金项目资助基于统计信息集的非高斯系统多目标优化控制及性能评估策略研究（61503271，61603267）；山西省自然科学基金项目资助 （）
