Compressive sensing based MIMO radar
The talk will present a new approach for colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS). CS-based MIMO radar exploit the sparsity of targets in the illuminated space to achieve the same localization performance as traditional MIMO radar but withsignificantly fewer measurements. Each receive node of the MIMO radar compresses the received signal via a linear transformation, referred to as measurement matrix. The compressively obtained samples are subsequently forwarded to a fusion center, where an $ell_1$ optimization problem isformulated and solved for target information. The measurement matrix plays an important role in CSrecovery algorithms. The talk will also discuss optimal design of the measurement matrix and also reduced complexity suboptimal constructions forit.