1. College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210003, China
2. College of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001,China
3. Jiangsu Provincial Engineering Research Center of Telecommunications and Network Technology, Nanjing, Jiangsu 210003, China
Abstract Based on the target spatial domain discretion, the target localization problem is formulated as a sparsity-seeking problem which can be solved by compressed sensing(CS) technique. In order to satisfy the robust recovery condition for CS theory requirement, an orthogonalization preprocessing method called LU decomposition is utilized to make the measurement matrix obey the restricted isometry property(RIP).Meanwhile, an improved orthogonal matching pursuit(IOMP) algorithm is proposed to recover the position of target, and the weighted centroid algorithm to enhance the positioning precision was also adopted. The simulation results illustrate that the average localization error of the proposed algorithm is less than other existing algorithms.
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2016, Vol. 37 
