Measurement Matrix Design for Compressive Sensing Based MIMO Radar

摘要

In colocated multiple-input multiple-output (MIMO) radar using compressivesensing (CS), a receive node compresses its received signal via a lineartransformation, referred to as measurement matrix. The samples are subsequentlyforwarded to a fusion center, where an L1-optimization problem is formulatedand solved for target information. CS-based MIMO radar exploits the targetsparsity in the angle-Doppler-range space and thus achieves the highlocalization performance of traditional MIMO radar but with many fewermeasurements. The measurement matrix is vital for CS recovery performance. Thispaper considers the design of measurement matrices that achieve an optimalitycriterion that depends on the coherence of the sensing matrix (CSM) and/orsignal-to-interference ratio (SIR). The first approach minimizes a performancepenalty that is a linear combination of CSM and the inverse SIR. The second oneimposes a structure on the measurement matrix and determines the parametersinvolved so that the SIR is enhanced. Depending on the transmit waveforms, thesecond approach can significantly improve SIR, while maintaining CSM comparableto that of the Gaussian random measurement matrix (GRMM). Simulations indicatethat the proposed measurement matrices can improve detection accuracy ascompared to a GRMM.