Target tracking algorithm for WSNs based on improved particle filtering

DING Ting-ting; GAO Mei-feng

doi:10.13873/J.1000-9787(2016)07-0140-03

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Target tracking algorithm for WSNs based on improved particle filtering

更新时间：2025-09-11

- Target tracking algorithm for WSNs based on improved particle filtering
- Vol. 35, Issue 7, Pages: 140-142+146(2016)
- 作者机构：
  
  江南大学轻工过程先进控制教育部重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)07-0140-03
  CLC： TN929.5;TP212.9;TP391.41
- Published：2016
- 稿件说明：
移动端阅览
[1]丁婷婷,高美凤.改进粒子滤波的无线传感器网络目标跟踪算法[J].传感器与微系统,2016,35(07):140-142+146.

DING Ting-ting, GAO Mei-feng. Target tracking algorithm for WSNs based on improved particle filtering[J]. 2016, 35(7): 140-142+146.
[1]丁婷婷,高美凤.改进粒子滤波的无线传感器网络目标跟踪算法[J].传感器与微系统,2016,35(07):140-142+146. DOI： 10.13873/J.1000-9787(2016)07-0140-03.

DING Ting-ting, GAO Mei-feng. Target tracking algorithm for WSNs based on improved particle filtering[J]. 2016, 35(7): 140-142+146. DOI： 10.13873/J.1000-9787(2016)07-0140-03.

摘要

针对粒子滤波（PF）重采样后造成的粒子枯竭现象的问题

提出了一种基于改进重采样的粒子滤波无线传感器网络目标跟踪算法。该算法避免了残差重采样算法中的残留粒子重采样问题

减少了计算时间;通过产生新的粒子

增加了粒子的多样性

从而改善了粒子枯竭现象。仿真实验结果表明:改进重采样的粒子滤波算法提高了目标跟踪精度

降低了跟踪误差。

Abstract

Aiming at particle impoverishment phenomenon caused by particle filtering resampling

a target tracking algorithm for WSNs based on improved resampling particle filtering is presented for the WSNs. The proposed algorithm avoids residual particle resampling problem

thus reduces calculation time; by producing new particles

diversity of particles is increased

so particle impoverishment phenomenon is improved. Simulation experimental results show that the improved resampling particle filtering algorithm improves target tracking precision and reduce tracking error.

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references

基于MCMC的改进粒子滤波算法 [J]. 席志红,付存利. 计算机工程与设计 . 2014(09)

分布式粒子滤波算法在目标跟踪中的应用 [J]. 谷静,史健芳. 传感器与微系统 . 2014(08)

一种改进重采样的粒子滤波算法 [J]. 常天庆,李勇,刘忠仁,董田沼. 计算机应用研究 . 2013(03)

权值选优粒子滤波的无线传感器网络目标跟踪 [J]. 刘刚,彭力. 传感器与微系统 . 2011(06)

基于粒子滤波的分布式目标跟踪算法 [J]. 黄小平,王岩,陈冰洁. 计算机工程 . 2011(04)

一种改进残差重采样算法的研究 [J]. 冯驰,赵娜,王萌. 哈尔滨工程大学学报 . 2010(01)

粒子滤波器重采样算法的分析与比较 [J]. 冯驰,王萌,汲清波. 系统仿真学报 . 2009(04)

基于优化组合重采样的粒子滤波算法 [J]. 邹国辉,敬忠良,胡洪涛. 上海交通大学学报 . 2006(07)

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