仅依赖连通度的压缩感知多目标定位方法

刘磊; 张建军; 陆阳; 卫星; 韩江洪

doi:10.11959/j.issn.1000-436x.2016103

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仅依赖连通度的压缩感知多目标定位方法

学术论文 | 更新时间：2024-06-05

- 仅依赖连通度的压缩感知多目标定位方法
- Multiple targets localization via compressive sensing from mere connectivity
- 通信学报 2016年37卷第5期页码：152-164
- 作者机构：
  
  1. 合肥工业大学计算机与信息学院，安徽合肥230009
  2. 教育部安全关键工业测控工程研究中心，安徽合肥 230009
- 作者简介：
  
  [ "刘磊（1982-），男，安徽合肥人，合肥工业大学博士生，主要研究方向为压缩感知和无线传感器网络定位。" ]
  [ "张建军（1963-），男，浙江宁波人，合肥工业大学教授、硕士生导师，主要研究方向为汽车电子、物联网工程、计算机集成制造。" ]
  [ "陆阳（1967-），男，安徽合肥人，合肥工业大学教授、博士生导师，主要研究方向为分布式控制、无线传感器网络、可靠性工程。" ]
  [ "卫星（1980-），男，安徽合肥人，合肥工业大学教授、硕士生导师，主要研究方向为物联网工程、离散事件动态系统等。" ]
  [ "韩江洪（1954-），男，江苏南京人，合肥工业大学教授、博士生导师，主要研究方向为计算机控制、离散事件控制理论和无线通信技术与理论等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61370088);国家国际科技合作专项基金资助项目(2014DFB10060)
- DOI：10.11959/j.issn.1000-436x.2016103
  中图分类号： TP393.1
- 网络出版日期：2016-05，
  
  纸质出版日期：2016-05-15
- 稿件说明：
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刘磊, 张建军, 陆阳, 等. 仅依赖连通度的压缩感知多目标定位方法[J]. 通信学报, 2016,37(5):152-164.

Lei LIU, Jian-jun ZHANG, Yang LU, et al. Multiple targets localization via compressive sensing from mere connectivity[J]. Journal on communications, 2016, 37(5): 152-164.
刘磊, 张建军, 陆阳, 等. 仅依赖连通度的压缩感知多目标定位方法[J]. 通信学报, 2016,37(5):152-164. DOI： 10.11959/j.issn.1000-436x.2016103.

Lei LIU, Jian-jun ZHANG, Yang LU, et al. Multiple targets localization via compressive sensing from mere connectivity[J]. Journal on communications, 2016, 37(5): 152-164. DOI： 10.11959/j.issn.1000-436x.2016103.

摘要

提出仅依赖连通度的多目标定位方法，将多目标定位问题转化为基于压缩感知的稀疏向量重构，解决室内参照物高密度分布的目标定位问题。定位方法仅以连通度为观测值，运用最小化l

范数法求解目标位置。当观1-测数据压缩为1 bit时，提出半正定松弛和不动点迭代法结合的目标求解算法。根据仿真实验结果，与MDS-MAP、DV-Hop和RSS-CS方法进行比较得出，仅连通度的非1-bit和1-bit量化的CS定位方法的平均定位误差小于1个网格，且2种方法占用的比特数只相当于RSS定位方法占用比特数的

和

。

Abstract

A multiple targets localization method was proposed from mere connectivity

and the multiple targets posi-tioning problem was converted to sparse vector resolving by compressive sensing theory

which was applied to the indoor localization of intensive references distribution.The connectivity to the references was collected as the only measurement data

and targets locations were figured out by minimum l

-norm algorithm.When measurement data was compress

ed tol 1 bit

the fixed point iteration algorithm combined with semi-definite relax was proposed to figure out targets locations.As for the simulation results

compared with MDS-MAP

DV-Hop and RSS-CS algorithms

the average location error is less than 1 grid by the mere connectivity of N -bit and 1-bit quantization CS localization

of which the occupied bit quan-tity are reduced to less than 4 times and 16 times of RSS localization observation value respectively.

关键词

Keywords

references

CHENG L , WU C D , ZHANG Y Z . Indoor robot localization based on wireless sensor networks [J ] . IEEE Transactions on Consumer Elec-tronics , 2011 , 57 ( 3 ): 1099 - 1104 .

LIU H B , YANG J , SIDHOM S , et al . Accurate WiFi based liza-tion for smartphones using peer assistance [J ] . IEEE Transactions on Mobile Computing , 2014 , 13 ( 10 ): 2199 - 2214 .

朱剑 , 赵海 , 徐久强 . 无线传感器网络中的定位模型 [J ] ．软件学报 , 2011 , 22 ( 7 ): 1612 - 1625 .

ZHU J , ZHAO H , XU J Q . Localization model in wireless net-work [J ] . Journal of Software , 2011 , 22 ( 7 ): 1612 - 1625 .

AHMAD EI A , SLIM Z , SOFIENE A , et al . Low-cost localization for multi-hop heterogeneous wireless sensor networks [J ] . IEEE Transac-tions on Signal Process , 2015 , 13 ( 7 ): 1199 - 1212 .

VOLKAN C , PETRO B , RICHARD G . Near-optimal bayesian locali-zation via incoherence and sparsity [C ] // International Conference of the IEEE Information Processing in Sensor Networks . San Francisco , c2009 : 205 - 216 .

ZHANG B W , CHENG X Z , ZHANG N , et al . Sparse target counting and localization in sensor networks based on compressive sens-ing [C ] // International Conference of the IEEE Computer Communica-tion(INFOCOM) . Shanghai,China , c2011 : 2255 - 2263 .

韩江洪 , 刘磊 , 卫星 . 信号场强压缩感知的传感器定位方法研究 [J ] ．仪器仪表学报 , 2014 , 35 ( 6 ): 1201 - 1208 .

HAN J H , LIU L , WEI X . Research on sensor localization method based on compressive sensing of signal strength [J ] . Chinese Journal of Scientific Instrument , 2014 , 35 ( 6 ): 1201 - 1208 .

赵春晖 , 许云龙 , 黄辉 . 基于LU分解的稀疏目标定位算法 [J ] ．电子与信息学报 , 2013 , 35 ( 9 ): 2234 - 2239 .

ZHAO C H , XU Y L , HUANG H . Localization algorithm of sparse targets based on LU-decomposition [J ] . Journal of Electronics & In-formation Technology , 2013 , 35 ( 9 ): 2234 - 2239 .

刘盼盼 , 李雷 , 王浩宇 . 压缩感知中基于变尺度法的贪婪重构算法研究 [J ] ．通信学报 , 2014 , 35 ( 12 ): 98 - 105 .

LIU P P , LI L , WANG H Y . Research on greedy reconstruction algo-rithms of compressed sensing based on variable metric method [J ] . Journal on Communications , 2014 , 35 ( 12 ): 98 - 105 .

XIAO F , SHA C H , et al . Noise-tolerant localization from incomplete range measurements for wireless sensor networks [C ] // In-ternational Conference of the IEEE Computer Communication(IN-FOCOM) . Hong Kong,China , c2015 : 2794 - 2802 .

GIORGIO Q , RICCARDO M , GIANLUIGI P , et al . Sensing,com-pression and recovery for wsns:sparse signal modeling and monitor-ing framework [J ] . IEEE Transactions on Wireless Communications , 2012 , 11 ( 10 ): 3447 - 3461 .

XIAO J , LUO Z , GIANNAKIS G B . Performance bounds for the rate-constrained universal decentralized estimators [J ] . IEEE Signal Process Letters , 2007 , 14 ( 1 ): 47 - 50 .

RIBEIRO A , GIANNAKIS G B . Bandwidth-constrained distributed estimation for wireless sensor networks–parti:Gaussian case [J ] . IEEE Transactions on Signal Process , 2006 , 54 ( 3 ): 1131 - 1143 .

WANG X H , QIU J , FAN J , et al . MDS-based localization scheme for large-scale WSNs within sparse anchor nodes [C ] // International Con-ference on Communications(ICC) . London,UK , c2015 : 6609 - 6614 .

杨辉强 , 李德英 , 李政 . 定向传感器网络中的最小化覆盖间隙和最大化网络生命时间问题的研究 [J ] ．电子学报 , 2010 , 38 ( 2 ): 138 - 141 .

YANG H Q , LI D Y , LI Z . Minimum coverage breach and maximum network lifetime in directional sensor networks [J ] . Acta Eletronica Si-nica , 2010 , 38 ( 2 ): 138 - 141 .

CANDES E , ROMBERG J , TAO T . Robust uncertainty principle:exact signal reconstruction from highly incomplete frequency information [J ] . IEEE Transactions on Information Theory , 2006 , 52 ( 4 ): 489 - 509 .

ZHOU G , HE T , SUDHA K , et al. . Models and solutions for radio irregularity in wireless sensor networks [J ] . ACM Transactions on Sensor Networks , 2006 , 2 ( 2 ): 221 - 262 .

戴琼海 , 付长军 , 季向阳 . 压缩感知研究 [J ] ．计算机学报 , 2011 , 34 ( 3 ): 425 - 434 .

DAI Q H , FU C J , JI X Y . Research on compressed sensing [J ] . Chinese Journal of Computers , 2011 , 34 ( 3 ): 424 - 434 .

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