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This paper proposes using the sparse-recovery (SR) based 2-D multiple-signal classification (MUSIC) to enhance the multi-target detection capability of high-frequency surface wave radars (HFSWRs). Usually, for wide-beam HFSWRs, target detection is first conducted in the range-Doppler spectrum; bearings are then estimated by super-resolution methods, such as MUSIC. Unfortunately, this approach can...