Computer Science ›› 2016, Vol. 43 ›› Issue (11): 160-163.doi: 10.11896/j.issn.1002-137X.2016.11.031

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Measurement Matrix Design for Multiple Target Localization Based on Compressive Sensing

GUO Yan, QIAN Peng, LI Ning and SUN Bao-ming   

  • Online:2018-12-01 Published:2018-12-01

Abstract: A compressive sensing based multiple target localization approach was proposed by exploiting the intrinsic sparse nature of the localization problem in wireless sensor networks.The sparsity in our localization approach is reflected by the locations of targets,which can be formulated as a sparse vector.We used the received signal strength (RSS) to achieve the target localization.It only requires a small number of measurements for accurately recovering the location vector by solving the 1-minimization program.Moreover,we proposed an improved measurement matrix design me-thod,which determines the distribution of sensors.Simulation results demonstrate that the localization accuracy and stability of the proposed measurement matrix design method have huge advantage in comparison with the random measurement matrix method widely used in CS-based localization.

Key words: Multiple target localization,Measurement matrix design,Compressive sensing,Wireless sensor networks

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