Computer Science ›› 2018, Vol. 45 ›› Issue (9): 161-165.doi: 10.11896/j.issn.1002-137X.2018.09.026

• Network & Communication • Previous Articles     Next Articles

Compressive Sensing Multi-target Localization Algorithm Based on Data Fusion

YANG Si-xing, GUO Yan, LI Ning, SUN Bao-ming, QIAN Peng   

  1. Institute of Communication Engineering,PLA University of Science and Technology,Nanjing 210007,China
  • Received:2017-07-12 Online:2018-09-20 Published:2018-10-10

Abstract: This paper proposd a new compressive sensing localization algorithm based on data fusion,which can utilize all kinds of the localization data at the same time.The proposed theory is based on the sparsity of the target number and compressive sensing theory,and it can greatly reduce the quantity of sampling compared with the traditional localization algorithms.The new algorithm consists of data pre-processing and data fusion based localization.At the first step,different kinds of measurements are transferred into the form which has the same level.Then the technique of multiple measurement vectors is used to recover the target vector.Compared with other algorithms,the proposed algorithm holds better performance in localization accuracy and robustness.

Key words: Compressive sensing, Data fusion, Multiple measurement vectors, Multiple target localization, Wireless sensor networks

CLC Number: 

  • TP393
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