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Sensors 2017, 17(6), 1246; doi:10.3390/s17061246

An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks

1
,
2
,
3,4
and
3,4,*
1
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2
School of Geodesy and Geomatics and the Collaborative Innovation Center for Geospatial Technology, Wuhan University, Wuhan 430079, China
3
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
4
Collaborative Innovation Center of Geospatial Technology (INNOGST), Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Received: 10 March 2017 / Revised: 18 May 2017 / Accepted: 22 May 2017 / Published: 30 May 2017

Abstract

In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position error. In the coarse localization phase, by formulating target localization as a sparse signal recovery problem, grids with recovery vector components greater than a threshold are chosen as the candidate target grids. In the fine localization phase, by partitioning each candidate grid, the target position in a grid is iteratively refined by using the minimum residual error rule and the least-squares technique. When all the candidate target grids are iteratively partitioned and the measurement matrix is updated, the recovery vector is re-estimated. Threshold-based detection is employed again to determine the target grids and hence the target population. As a consequence, both the target population and the position estimation accuracy can be significantly improved. Simulation results demonstrate that the proposed approach achieves the best accuracy among all the algorithms compared. View Full-Text
Keywords: compressive sensing; positioning; received signal strength; target population; wireless local area network compressive sensing; positioning; received signal strength; target population; wireless local area network
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Yan, J.; Yu, K.; Chen, R.; Chen, L. An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks. Sensors 2017, 17, 1246.

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