Spread Spectrum Code Design for MIMO Radar Estimation Using Compressive Sensing Modeling

We consider the problem of multipletarget estimation using a collocated multiple-input multiple-output (MIMO) radar system. We employ sparse modeling to estimate the unknown target parameters (delay, Doppler) using a MIMO radar system that transmits frequencyhopping waveforms. We formulate the measurement model using a block sparse representation. We adaptively design the transmit waveform parameters (frequencies, amplitudes) to improve the estimation performance. Firstly, we derive analytical expressions for the correlations between the different blocks of columns of the sensing matrix. Using these expressions, we compute the block coherence measure of the dictionary. We use this measure to optimally design the sensing matrix by selecting the hopping frequencies for all the transmitters. Secondly, we adaptively design the amplitudes of the transmitted waveforms during each hopping interval to improve the estimation performance. Further, we employ compressive sensing to conduct accurate estimation from far fewer samples than