杨思星,郭艳,刘杰,孙保明.基于动态格点的压缩感知目标计数和定位算法[J].计算机科学,2018,45(1):223-227
基于动态格点的压缩感知目标计数和定位算法
Dynamic Grid Based Sparse Target Counting and Localization Algorithm Using Compressive Sensing
投稿时间:2016-11-05  修订日期:2017-03-26
DOI:10.11896/j.issn.1002-137X.2018.01.039
中文关键词:  动态格点,压缩感知,格点失配,多目标定位,目标计数
英文关键词:Dynamic grid,Compressive sensing,Off-grid,Multiple target localization,Target counting
基金项目:本文受国家自然科学基金项目(61571463,61371124,61472445),江苏省自然科学基金(BK20171401)资助
作者单位E-mail
杨思星 陆军工程大学通信工程学院 南京210007 875413714@qq.com 
郭艳 陆军工程大学通信工程学院 南京210007 guoyan_2000@sina.com 
刘杰 武警部队 北京100089  
孙保明 陆军工程大学通信工程学院 南京210007  
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中文摘要:
      基于压缩感知技术的无线传感器网络定位,一般将定位区域划分为一定数目的网格并假定目标位于网格中心,然后通过求解一个1范数最小化问题来获得目标的位置。事实上,目标的随机性导致其很难位于网格中心,此时假定的变换基将无法稀疏表示位置信号,从而造成字典失配,使得定位精度下降。因此,提出一种基于动态格点的压缩感知定位算法。该算法能够自适应地调整格点的划分,使目标位于网格中心处。在求解过程中,该算法将复杂的优化问题转化成字典的更新和位置向量的求解两个部分的迭代来完成,同时实现了目标的计数和定位功能。仿真结果证明,与传统的压缩感知定位算法相比,所提算法在目标计数和定位方面都有更好的性能。
英文摘要:
      According to the localization algorithm based on Compressive Sensing (CS) in Wireless Sensor Network (WSN),the localization area is generally divided into a number of grids and the targets are located in the grid points.Then the locations of the targets can be obtained by 1-minimization algorithm.Practically,the assumption of the targets located in the grid points is almost impossible,which will make the location vector not sparse,and may lead to dictionary mismatch and cause error.As a result,a novel framework of localization approach based on dynamic grid was proposed.This approach can adaptively adjust the grid to make the targets exactly in the grid points.The proposed algorithm is solved by the iteration between the dictionary update and the obtaining of the location vector.At the same time,the algorithm can obtain the performance of both sparse target counting and localization.Simulation results show that the new proposed approach has advantages in both target counting and localization accuracy compared with the traditional CS-based algorithms.
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