Paper Info
Title
An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks.
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.
Year
DOI
Venue
2017
10.3390/s17061246
SENSORS
Keywords
Field
DocType
compressive sensing,positioning,received signal strength,target population,wireless local area network
Residual,Population,Wireless,Matrix (mathematics),Algorithm,Electronic engineering,Wi-Fi,Engineering,RSS,Compressed sensing,Grid
Journal
Volume
Issue
ISSN
17
6
1424-8220
Citations 
PageRank 
References 
0
0.34
27
Authors
4
Name
Order
Citations
PageRank
Jun Yan1245.17
Kegen Yu255657.05
Ruizhi Chen340255.33
Liang Chen421.72