Optimization of indoor positioning system for sensor networks based on particle swarm optimization algorithm

ZHANG Lei; HUANG Ru; YUAN Wei-na

doi:10.13873/J.1000-9787(2017)04-0061-04

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Optimization of indoor positioning system for sensor networks based on particle swarm optimization algorithm

更新时间：2025-09-11

- Optimization of indoor positioning system for sensor networks based on particle swarm optimization algorithm
- Vol. 36, Issue 4, Pages: 61-64(2017)
- 作者机构：
  
  华东理工大学信息科学与工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2017)04-0061-04
  CLC： TN929.5;TP18;TP212.9
- Published：2017
- 稿件说明：
移动端阅览
[1]张磊,黄如,袁伟娜.基于粒子群算法的传感器网络室内定位系统优化[J].传感器与微系统,2017,36(04):61-64.

ZHANG Lei, HUANG Ru, YUAN Wei-na. Optimization of indoor positioning system for sensor networks based on particle swarm optimization algorithm[J]. 2017, 36(4): 61-64.
[1]张磊,黄如,袁伟娜.基于粒子群算法的传感器网络室内定位系统优化[J].传感器与微系统,2017,36(04):61-64. DOI： 10.13873/J.1000-9787(2017)04-0061-04.

ZHANG Lei, HUANG Ru, YUAN Wei-na. Optimization of indoor positioning system for sensor networks based on particle swarm optimization algorithm[J]. 2017, 36(4): 61-64. DOI： 10.13873/J.1000-9787(2017)04-0061-04.

摘要

通过接收信号强度指示（RSSI）和欧氏距离的非线性函数映射关系来进行弱移动目标的距离估计。以最大似然估计（MLE）法为基础

结合电磁波在自由空间中的传播特性

重新构建基于粒子群优化（PSO）定位算法的适应度函数来提高无线定位精度。并提出了一种惯性权重优化的自适应学习机制来优化全局搜索能力和局部搜索精度

提升定位算法的容错能力。测试结果表明:本室内定位算法具有抗干扰强、鲁棒性好和无线定位精度高等优点。

Abstract

The nonlinear function mapping relationship between RSSI and Euclidean distance is used to estimate distance of weak mobile target. This system improves positioning precision by rebuilding fitness function based on PSO positioning algorithm

on the basis of maximum likelihood estimation（ MLE） and combines with characteristics of electromagnetic wave propagation in free space. Besides

an adaptive learning mechanism of inertia weight optimization is put forward to optimize global searching ability and local searching precision. The fault tolerance of localization algorithm is promoted. With experiment on CC2530

it is proved to have the advantages of strong antiinterference

good robustness and high precision of wireless localization.

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references

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基于RSSI校正的无线传感器网络定位算法 [J]. 文春武,宋杰,姚家振. 传感器与微系统 . 2014(12)

基于超宽频距离传感器的移动目标定位系统 [J]. 邵磊,赵京,张乃龙. 传感器与微系统 . 2013(11)

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无线传感器网络定位优化算法及其仿真 [J]. 彭燕. 计算机与数字工程 . 2011(03)

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