Compressed Sensing MIMO Radar Waveform Optimization Without Signal Recovery

It has been proved that compressed sensing (CS) is an efficient technique in MIMO radar system due to their ability to significantly reduce the computational burden. In this paper, we present an iterative waveform optimization algorithm for compressed sensing MIMO radar without signal reconstruction. Using prior information of target and clutter, the transmitted waveforms and the receiving filters are optimized alternatively. By maximizing SINR, the high detection performance of compressed sensing MIMO radar is guaranteed. Without reconstructing the signal, the complexity in receiver can also be decreased. We calculate the SINR of MIMO radar waveforms and compare with its own upper bounds and the SINR corresponding to the LFM waveforms. The numerical results show that using the algorithm in waveform design process, the SINR of compressed sensing MIMO radar waveforms is improved significantly compare to the LFM waveforms.