Two-Stage Fast Matching Pursuit Algorithm for Multi-Target Localization.

For large-scale high-dimensional positioning scenes, the massive number of grid points brings challenges to the multi-target positioning algorithms based on compressed sensing. To cope with the challenges, a fast multi-target localization method based on direction of arrival is proposed. A compressed sensing model is constructed for multi-target localization based on the DOA sequence measured by positioning nodes. Then, a two-stage fast matching pursuit algorithm is presented for sparse reconstruction, which consists of preliminary estimation and supports rectification. A process similar to orthogonal matching pursuit algorithm is adopted to get preliminary estimate result, but no nonlinear operations is employed for complexity reduction. Then another iterative process is carried out to rectify the chosen supports in preliminary result sequentially. Simulation results verify the effectiveness and accuracy of the proposed method for multi-target localization.