计算机科学 ›› 2018, Vol. 45 ›› Issue (1): 223-227.doi: 10.11896/j.issn.1002-137X.2018.01.039
杨思星,郭艳,刘杰,孙保明
YANG Si-xing, GUO Yan, LIU Jie and SUN Bao-ming
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。
[1] RALLAPALLI S,QIU L,ZHANG Y,et al.Exploiting temporal stability and low-rank structure for localization in mobile networks[C]∥The Sixteenth International Conference on Mobile Computing and Networking.ACM,2010:161-172. [2] PANWAR A,KUMAR S A.Localization schemes in wireless sensor networks[C]∥Proc 2nd International Conference on Advanced Computing & Communication Technologies.IEEE,2012:443-449. [3] SHI G M,LIU D H,GAO D H,et al.Advances in theory and application of compressed sensing[J].Acta Electronica Sinica,2009,37(5):1070-1081.(in Chinese) 石光明,刘丹华,高大化,等.压缩感知理论及其研究进展[J].电子学报,2009,37(5):1070-1081. [4] HE F H,YU Z J,LIU H T.Multiple target localization via compressed sensing in wireless sensor networks[J].Journal of Electronics and Information Technology,2012,34(3):716-721.(in Chinese) 何风行,余志军,刘海涛.基于压缩感知的无线传感器网络多目标定位算法[J].电子与信息学报,2012,34(3):716-721. [5] CANDS E J.Compressive sampling[C]∥Proceedings of the International Congress of Mathematicians.2006:1433-1452. [6] JI S,XUE Y,CARIN L.Bayesian compressive sensing[J].IEEE Transactions on Signal Processing,2008,56(6):2346-2356. [7] WU X P,LIU M Y.In-situ soil moisture sensing:measurement scheduling and estimation using compressive sensing[C]∥IEEE Conference on Information Processing in Sensor Networks (IPSN).2012:2012:1-12. [8] FENG C,VALAEE S,TAN Z.Multiple target localization usingcompressive sensing[C]∥Global Telecommunications Confe-rence.IEEE,2009:1-6. [9] CHEN F,AU W S A,VALAE E S,et al.Compressive Sensing Based Positioning Using RSS of WLAN Access Points[C]∥ Proceedings of the 29th Conference on Information Communications(INFOCOM’10).2010:14-19. [10] ZHANG B,CHENG X,ZHANG N,et al.Sparse target counting and localization in sensor networks based on compressive sen-sing[C]∥INFOCOM,2011 .2011:2255-2263. [11] PENG Q,YAN G,NING L,et al(1)An Improved Sensor Deployment Scheme for Multiple Target Localization using Compressive Sensing[C]∥International Conference on Electronics Information & Emergency Communication.2015:384-387. [12] CANDES E J,ROMBERG J,TAO T.Robust uncertainty principles:exact signal reconstruction from highly incomplete frequency information[J].IEEE Transactions on Information Theo-ry,2006,2(2):489-509. [13] CANDES E J,WAKIN M B,BOYD S.Enhancing sparsity by reweighted minimization[J].Journal of Fourier Analysis and Applications,2008,14(5):877-905. [14] AUSTIN C D,ASH J N,MOSES R L.Dynamic dictionary algorithms for model order and parameter estimation[J].IEEE Transactions on Signal Processing,2013,61(20):5117-5130. [15] LIU K,YU J J,HUANG Q H.Bi-object device-free localization based on compressive sensing[J].Journal of Electronics & Information Technology,2014,36(4):862-867.(in Chinese) 刘凯,余君君,黄青华.基于压缩感知的免携带设备双目标定位算法[J].电子与信息学报,2014,36(4):862-867. |
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