期刊文献+

基于压缩感知的无线传感器网络多目标定位算法 被引量:40

Multiple Target Localization via Compressed Sensing in Wireless Sensor Networks
在线阅读 下载PDF
导出
摘要 目标定位是无线传感器网络的重要应用场景。该文提出了一种将压缩感知应用于无线传感器网络多目标定位的方法,把基于网格的多目标定位问题转化为压缩感知问题。应用多分辨率分析的思想,设计了迭代回溯的压缩感知算法,该方法的特点是可同时进行多目标定位,并且大大减少了网络通信的数据量从而延长网络寿命,代价是融合中心的算法复杂度的增加。仿真结果显示,采用迭代回溯算法定位精度提高了50%以上,具有较好的多目标定位效果。 Target localization is one of the most challenging and important issues in Wireless Sensor Networks(WSNs).A multiple target localization method is proposed in WSNs.The multiple target localization issue is transformed into compressed sensing issue by designing iteration backtracking algorithm using multi-resolution analysis idea.The achievement of this algorithm is to save the energy of WSN nodes,by minimizing inter-node communication,in the result of which the lifetime of the WSN is prolonged,at the cost of increasing the computation complexity in the fusion center instead.Emulation results demonstrated that the localization performance is improved by more than 50% by the proposed algorithm.
出处 《电子与信息学报》 EI CSCD 北大核心 2012年第3期716-721,共6页 Journal of Electronics & Information Technology
基金 国家973计划项目(2011CB302901) 国家科技重大专项(2010ZX03006-004)资助课题
关键词 多目标定位 无线传感器网络 压缩感知 Multiple target localization Wireless Sensor Networks(WSNs) Compressed sensing
  • 相关文献

参考文献11

  • 1Donoho D.Compressed sensing[J].IEEE Transactions onInformation Theroy,2006,52(4):1289-1306.
  • 2Candès E,Romberg J,and Tao T.Robust uncertaintyprinciples:exact signal reconstruction from highly incompletefrequency information[J].IEEE Transactions on InformationTheory,2006,52(2):489-509.
  • 3Patwari N,Ash J N,Kyperountas S,et al..Locating thenodes:cooperative localization in wireless sensor networks[J].IEEE Signal Processing Magazine,2005,22(4):54-69.
  • 4Malioutov D,Cetin M,and Willsky A S.A sparse signalreconstruction perspective for source localization with sensorarrays[J].IEEE Transactions on Signal Processing,2005,53(8):3010-3022.
  • 5Cevher V,Duarte M F,and Baraniuk R G.Distributedtarget localization via spatial sparsity[C].Proceedings of theEuropean Signal Processing Conference,Lausanne,Switzerland,Aug.25-29,2008:25-29.
  • 6Feng Chen,Valaee S,and Tan Zhen-hui.Multiple targetlocalization using compressive sensing[C].IEEE GlobalCommunications Conference,Honolulu,HI,USA,Nov.30-Dec.4,2009:1-6.
  • 7Candès E and Romberg J.Sparsity and incoherence incompressive sampling[J].Inverse Problems,2007,23(3):969-985.
  • 8Candès E and Plan Y.A probabilistic and RIPless theory ofcompressed sensing[J].IEEE Transactions on InformationTheory,2011,57(11):7235-7254.
  • 9Blumensath T and Davies M E.Iterative hard thresholdingfor compressed sensing[J].Applied and ComputationalHarmonic Analysis,2009,27(3):265-274.
  • 10Dai Wei and Milenkovic O.Subspace pursuit for compressivesensing signal reconstruction[J].IEEE Transactions onInformation Theory,2009,55(5):2230-2249.

同被引文献330

引证文献40

二级引证文献169

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部