Compressed Sensing Based Two-phase Multiple Target Localization Algorithm for Wireless Sensor Network

摘要

Localization is one of fundamental technologies in Wireless Sensor Network (WSN). The spatial sparsity of the targets can be employed to address the problem of the multiple target localization based on Compressed Sensing (CS). In the traditional CS based localization algorithm, owing to the large amounts of grids obtained by dividing the monitored area into small grids, the dimension of the sensing matrix and the computation complexity are both high and the localization accuracy and the response time are seriously influenced. In this paper a novel multiple target localization algorithm named CS based Two-phase Multiple Target Localization algorithm combined with Voronoi Diagram (VD-TMTL) is proposed. VD-TMTL consists of two phases. In the large-scale localization phase, Voronoi Diagram based Greedy Matching Pursuit method is used to search for the candidate grids in the local subareas. In the fine localization phase, the candidate grids are divided into the fine grids relying on the Least Grid Side Length theorem. Then the sparse reconstruction is executed and the locations of the targets are estimated as the center of the fine grids. The simulation results show that the proposed algorithm can reduce the time complexity and improve the localization accuracy effectively.