Parameter estimation for sparse targets in phased-MIMO radar

Parameter estimation using phased-multiple-input multiple-output (MIMO) radar is investigated in this study, where transmitting antennas are partitioned into subarrays to provide both waveform diversity and high coherent processing gain. By exploiting the target sparsity in the spatial domain, a compressed sensing-based estimation method is proposed to jointly estimate the direction of arrivals and scattering coefficients of multiple targets in phased-MIMO radar. Cramer-Rao lower bound is derived from setting a performance limit on the presented algorithm, and simulation results are provided to validate its efficiency. Numerical examples reveal that efficient estimation can be obtained when the received signal-to-noise ratio exceeds a threshold at the level of about 5dB. Also, the authors also show that the number of subarrays and the size of each subarray constitute a fundamental trade-off in improving the estimation performance.