Performance of Compressed Sensing MIMO Radar Based on Low-Rank Matrix Recovery

Compressed sensing (CS) techniques have been successfully applied to multi-input multi-output (MIMO) radars to drastically reduce the sampling rates required for acquiring data. In this work, a CS MIMO radar is derived by employing a matrix recovery algorithm exploiting the low-rank structure of the data matrix based on linearly compressed measurements. Compared to a MIMO radar based on low-rank matrix completion, the proposed approach is seen to provide superior data reconstruction and target estimation performance at lower sampling rates.