无线传感器网络中基于自适应网格的多目标定位算法

doi:10.11959/j.issn.1000-436x.2019129

通信学报 ›› 2019, Vol. 40 ›› Issue (7): 197-207.doi: 10.11959/j.issn.1000-436x.2019129

无线传感器网络中基于自适应网格的多目标定位算法

王天荆,李秀琴(),白光伟,沈航

南京工业大学计算机科学与技术学院，江苏南京 211816

修回日期:2019-02-28 出版日期:2019-07-25 发布日期:2019-07-30
作者简介:王天荆（1977- ），女，江苏扬州人，博士，南京工业大学副教授、硕士生导师，主要研究方向为信号处理、无线网络和最优化方法。|李秀琴（1994- ），女，江苏南京人，南京工业大学硕士生，主要研究方向为无线传感器网络和最优化方法。|白光伟（1961- ），男，陕西西安人，博士，南京工业大学教授、硕士生导师，主要研究方向为无线网络、数据隐私和网络编码。|沈航（1984- ），男，江苏南京人，博士，南京工业大学副教授、硕士生导师，主要研究方向为无线网络、数据隐私和网络编码。
基金资助:
国家自然科学基金资助项目(61501224);国家自然科学基金资助项目(61502230);国家自然科学基金资助项目(61602235);国家自然科学基金资助项目(61802176);江苏省自然科学基金资助项目(BK20161007);江苏省自然科学基金资助项目(BK20150960);江苏省研究生科研与实践创新计划基金资助项目(SJCX18_0339)

Multi-target localization algorithm based on adaptive grid in wireless sensor network

Tianjing WANG,Xiuqin LI(),Guangwei BAI,Hang SHEN

School of Computer Science and Technology,Nanjing Tech University,Nanjing 211816,China

Revised:2019-02-28 Online:2019-07-25 Published:2019-07-30
Supported by:
The National Natural Science Foundation of China(61501224);The National Natural Science Foundation of China(61502230);The National Natural Science Foundation of China(61602235);The National Natural Science Foundation of China(61802176);The Natural Science Foundation of Jiangsu Province(BK20161007);The Natural Science Foundation of Jiangsu Province(BK20150960);Postgraduate Research ＆ Practice Innovation Program of Jiangsu Province(SJCX18_0339)

摘要/Abstract

摘要：

针对无线传感器网络中基于RSS的多目标定位具有天然稀疏性的问题，提出了基于自适应网格的多目标定位算法，将多目标定位问题分解为大尺度网格定位和自适应网格定位2个阶段。大尺度网格定位阶段根据序贯压缩感知原理确定最优观测次数，再利用lp (0＆lt; p＆lt;1)最优化重构出存在目标的初始网格；自适应网格定位阶段根据压缩感知原理自适应划分初始网格，再利用lp最优化重构出目标的精确位置。仿真结果表明，相较于传统的基于压缩感知的多目标定位算法，所提算法在目标个数未知的场景下具有更高的定位精度和更低的定位时延，且更适合大规模无线传感器网络的多目标定位问题。

关键词: 无线传感器网络, 多目标定位, 压缩感知, 序贯压缩感知, 自适应网格

Abstract:

The RSS-based multi-target localization has the natural property of the sparsity in wireless sensor networks.A multi-target localization algorithm based on adaptive grid in wireless sensor networks was proposed,which divided the multi-target localization problem into two phases:large-scale grid-based localization and adaptive grid-based localization.In the large-scale grid-based localization phase,the optimal number of measurements was determined due to the sequential compressed sensing theory,and then the locations of the initial candidate grids were reconstructed by applying lp (0＆lt; p＆lt;1) optimization.In the adaptive grid-based localization phase,the initial candidate grids were adaptively partitioned according to the compressed sensing theory,and then the locations of the targets were precisely estimated by applying lpoptimization once again.Compared with the traditional multi-target localization algorithm based on compressed sensing,the simulation results show that the proposed algorithm has higher localization accuracy and lower localization delay without foreknowing the number of targets.Therefore,it is more appropriate for the multi-target localization problem in the large-scale wireless sensor networks.

Key words: wireless sensor network, multi-target localization, compressed sensing, sequential compressed sensing, adaptive grid

中图分类号:

TP393

王天荆,李秀琴,白光伟,沈航. 无线传感器网络中基于自适应网格的多目标定位算法[J]. 通信学报, 2019, 40(7): 197-207.

Tianjing WANG,Xiuqin LI,Guangwei BAI,Hang SHEN. Multi-target localization algorithm based on adaptive grid in wireless sensor network[J]. Journal on Communications, 2019, 40(7): 197-207.

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描述	符号	数值
功率/dBm	p_t	- 40
参考距离	d₀	1
路径损耗系数	η	2
SCS判别门限值	τ	0.05
稀疏判别门限值	γ	0.5

区域	合并初始网格的定位时间/s	不合并初始网格的定位时间/s
c₁	0.255 62	0.896 93
c₂	0.184 86	0.449 48
c₃	0.227 12	0.486 58

无线传感器网络中基于自适应网格的多目标定位算法

Multi-target localization algorithm based on adaptive grid in wireless sensor network

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