基于压缩感知的多目标定位中的测量矩阵设计

计算机科学 ›› 2016, Vol. 43 ›› Issue (11): 160-163.doi: 10.11896/j.issn.1002-137X.2016.11.031

基于压缩感知的多目标定位中的测量矩阵设计

郭艳,钱鹏,李宁,孙保明

解放军理工大学通信工程学院南京210007,解放军理工大学通信工程学院南京210007,解放军理工大学通信工程学院南京210007,解放军理工大学通信工程学院南京210007

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受国家自然科学基金项目(61571463,61371124,61272487,61472445,61201217)资助

Measurement Matrix Design for Multiple Target Localization Based on Compressive Sensing

GUO Yan, QIAN Peng, LI Ning and SUN Bao-ming

Online:2018-12-01 Published:2018-12-01

摘要/Abstract

摘要： 根据传感器网络中定位问题天然的稀疏性,研究了基于压缩感知理论的多目标定位方法。首先将目标位置信息表示成一个稀疏向量,将定位问题转化为向量估计问题。通过部署少量传感器测量接收信号的强度值,求解一个₁范数最优化问题便可精确地重构出位置向量。相对于当前压缩感知定位中常用的稀疏随机测量矩阵,提出了一种改进的测量矩阵设计方法,指示传感器节点进行有规律、均匀的部署。仿真结果表明,相较于传统随机测量矩阵,改进测量矩阵在定位精确度和稳定性上都体现了巨大优势。

关键词: 多目标定位,测量矩阵设计,压缩感知,传感器网络

Abstract: A compressive sensing based multiple target localization approach was proposed by exploiting the intrinsic sparse nature of the localization problem in wireless sensor networks.The sparsity in our localization approach is reflected by the locations of targets,which can be formulated as a sparse vector.We used the received signal strength (RSS) to achieve the target localization.It only requires a small number of measurements for accurately recovering the location vector by solving the ₁-minimization program.Moreover,we proposed an improved measurement matrix design me-thod,which determines the distribution of sensors.Simulation results demonstrate that the localization accuracy and stability of the proposed measurement matrix design method have huge advantage in comparison with the random measurement matrix method widely used in CS-based localization.

Key words: Multiple target localization,Measurement matrix design,Compressive sensing,Wireless sensor networks

郭艳,钱鹏,李宁,孙保明. 基于压缩感知的多目标定位中的测量矩阵设计[J]. 计算机科学, 2016, 43(11): 160-163. https://doi.org/10.11896/j.issn.1002-137X.2016.11.031

GUO Yan, QIAN Peng, LI Ning and SUN Bao-ming. Measurement Matrix Design for Multiple Target Localization Based on Compressive Sensing[J]. Computer Science, 2016, 43(11): 160-163. https://doi.org/10.11896/j.issn.1002-137X.2016.11.031

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