基于相位偏移的压缩感知无源多目标定位方法

doi:10.7523/j.ucas.2022.066

中国科学院大学学报 ›› 2024, Vol. 41 ›› Issue (2): 241-248.DOI: 10.7523/j.ucas.2022.066

• 电子信息与计算机科学 • 上一篇下一篇

基于相位偏移的压缩感知无源多目标定位方法

盛金锋, 李宁, 郭艳, 陈承, 李华静

陆军工程大学通信工程学院, 南京 210007

收稿日期:2022-01-06 修回日期:2022-06-21 发布日期:2022-06-27
通讯作者: 李宁,E-mail:js_ningli@sina.com
基金资助:
国家自然科学基金(61871400)和江苏省自然科学基金(BK20211227)资助

Device-free multi-target localization method using phase-shift-based compressive sensing

SHENG Jinfeng, LI Ning, GUO Yan, CHEN Cheng, LI Huajing

College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China

Received:2022-01-06 Revised:2022-06-21 Published:2022-06-27

摘要/Abstract

摘要： 无源定位作为一种新兴的定位技术，是安防监控、入侵检测和接触跟踪等被动传感领域的研究热点。其通过分析无源目标对无线链路的阴影效应来定位目标。相位是无线信号的一个重要特性，比信号强度更具细粒度。为提升定位性能，利用无线链路相位信息，提出基于相位偏移的压缩感知无源多目标定位方法。该方法将接收信号相位偏移值作为观测数据，结合变分贝叶斯推理，恢复目标位置稀疏向量。仿真实验结果表明，在6.5 m×6.5 m的监测区域中，基于接收信号强度的定位方法平均定位误差为0.579 0 m，而该方法的平均定位误差为0.254 7 m，定位精度提升超过1倍，且该方法具有较强的鲁棒性。

关键词: 无源定位, 压缩感知, 相位偏移, 变分贝叶斯推理

Abstract: Device-free localization(DFL),as a new localization technology,is a hotspot in passive sensing such as security monitoring,intrusion detection and contact tracking.It locates the target by analyzing the shadow effect of passive target on wireless link.Phase is an important characteristic of wireless signal,which is more fine-grained than signal strength.To improve the localization performance,we use phase information of wireless links and propose a device-free multi-target localization method using phase shift based compressive sensing.In this method, the phase shift of received signal is taken as the observation data, and the sparse vector of target position is recovered by variational Bayesian inference.Simulation results show that in the monitoring area of 6.5 m×6.5 m,the average localization error of RSS method is 0.579 0 m, while the average localization error of this method is 0.254 7 m,the localization accuracy is improved by more than one times,and it can achieve robust DFL.

Key words: device-free localization, compressive sensing, phase shift, variational Bayesian inference

中图分类号:

TN911.7

盛金锋, 李宁, 郭艳, 陈承, 李华静. 基于相位偏移的压缩感知无源多目标定位方法[J]. 中国科学院大学学报, 2024, 41(2): 241-248.

SHENG Jinfeng, LI Ning, GUO Yan, CHEN Cheng, LI Huajing. Device-free multi-target localization method using phase-shift-based compressive sensing[J]. Journal of University of Chinese Academy of Sciences, 2024, 41(2): 241-248.

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基于相位偏移的压缩感知无源多目标定位方法

Device-free multi-target localization method using phase-shift-based compressive sensing

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