论文:2020,Vol:38,Issue(1):31-39
引用本文:
李晓强, 陈建峰, 张蓉蓉, 温洋, 谭伟杰. 基于快速正交匹配追踪的无线传感网中目标定位算法[J]. 西北工业大学学报
LI Xiaoqiang, CHEN Jianfeng, ZHANG Rongrong, WEN Yang, TAN Weijie. Target Localization Algorithm of Wireless Sensor Network Based on Fast Orthogonal Matching Pursuit in[J]. Northwestern polytechnical university

基于快速正交匹配追踪的无线传感网中目标定位算法
李晓强, 陈建峰, 张蓉蓉, 温洋, 谭伟杰
西北工业大学 航海学院, 陕西 西安 710072
摘要:
高效准确的多目标定位是无线传感器网的基本任务之一。传统基于贪婪类的稀疏表示方法在多目标定位中计算效率不高。针对该问题,提出一种基于QR分解的快速正交匹配追踪的多目标定位算法。该算法对无线传感器覆盖区域进行网格划分来设计过完备字典,从而将多目标定位问题转化为稀疏信号恢复问题。该方法利用了传感器接收目标信号强度的稀疏特性,然后使用快速正交匹配追踪来恢复测量值,进而通过稀疏性来定位目标。通过列满秩矩阵的QR分解思想,利用递归形式来对子字典矩阵求逆,避免了传统方法中对该矩阵的直接求逆,使得运算量大为降低。仿真结果表明,与传统的正交匹配追踪压缩感知重构方法相比,该方法不损失定位精度,提高了运算效率。
关键词:    无线传感网    接收信号强度    快速正交匹配追踪    列满秩矩阵QR分解    目标定位   
Target Localization Algorithm of Wireless Sensor Network Based on Fast Orthogonal Matching Pursuit in
LI Xiaoqiang, CHEN Jianfeng, ZHANG Rongrong, WEN Yang, TAN Weijie
School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
Efficient localization of multiple targets is one of the basic technical problems in wireless sensor networks (WSN). The traditional sparse representation method based on greedy class is not efficient in multi-target positioning. Aiming at this problem, a multi-target localization algorithm based on QR decomposition for fast orthogonal matching pursuit is proposed. The algorithm meshes the wireless sensor coverage area to design an over-complete dictionary, which transforms the multi-target localization problem into a sparse signal recovery problem. The method utilizes the sensor to receive the sparse characteristics of the target signal strength, and then uses fast orthogonal matching pursuit to recover the measured values, thereby localization the target by sparsity. Through the QR decomposition of the column full rank matrix, the recursive form is used to invert the sub-dictionary matrix, thus avoiding the direct inversion of the matrix in the traditional method, so that the computational complexity is greatly reduced. The simulation results show that compared with the traditional orthogonal matching pursuit compressed sensing reconstruction method, this method does not lose the localization accuracy and improves the computational efficiency.
Key words:    wireless sensor networks    received signal strength    fast orthogonal matching pursuit    column full rank matrix QR decomposition    target localization   
收稿日期: 2019-01-20     修回日期:
DOI: 10.1051/jnwpu/20203810031
基金项目: 国家自然科学基金-浙江大学联合基金(U1609204)资助
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作者简介: 李晓强(1978-),西北工业大学博士研究生,主要从事无线传感网、阵列信号处理研究。
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