南京邮电大学学报（自然科学版）2017，Vol.37Issue(5)：1-6,6.DOI:10.14132/j.cnki.1673-5439.2017.05.001
基于改进粒子滤波的无线传感器网络目标跟踪算法
Target tracking algorithm for wireless sensor networks based on improved particle filter
摘要
Abstract
Aiming at particle degradation and sample depletion defects in particle filter for existing wireless sensor network target tracking algorithm,an improved particle filter target tracking algorithm is proposed.By using the ensemble Kalman method to obtain the proposed distribution function of the target state,the target state is estimated by the form of the set and the distribution function is often corrected by combining with the latest observation data.Finally,the target tracking accuracy is improved.At the resampling stage,the artificial fish swarm algorithm is used to improve the distribution of the particles to make the particles be closer to the real value,increasing the numbers of effective particles and the particle diversity,meanwhile improving the phenomenon of particle depletion.The simulation results show that the improved algorithm is superior to the existing target tracking algorithms in tracking accuracy,stability and reliability.关键词
粒子滤波/无线传感器网络/目标跟踪/集合卡尔曼滤波/人工鱼群Key words
particle filter/wireless sensor networks/target tracking/ensemble Kalman filter/artificial fish swarm分类
信息技术与安全科学引用本文复制引用
邬春明,宫皓泉,王艳娇,赵星翰,郭立杰,梁玉珠..基于改进粒子滤波的无线传感器网络目标跟踪算法[J].南京邮电大学学报（自然科学版）,2017,37(5):1-6,6.基金项目
国家自然科学基金(61501107)资助项目 （61501107）
