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Distributed MIMO radar is known to achieve superior sensing performance byemploying widely separated antennas. However, it is challenging to implement alow-complexity distributed MIMO radar due to the complex operations at both thereceivers and the fusion center. This work proposed a low-bit quantizeddistributed MIMO (LiQuiD-MIMO) radar to significantly reduce the burden ofsignal acquisition and data transmission. In the LiQuiD-MIMO radar, thewidely-separated receivers are restricted to operating with low-resolution ADCsand deliver the low-bit quantized data to the fusion center. At the fusioncenter, the induced quantization distortion is explicitly compensated viadigital processing. By exploiting the inherent structure of our problem, aquantized version of the robust principal component analysis (RPCA) problem isformulated to simultaneously recover the low-rank target information matricesas well as the sparse data transmission errors. The least squares-based methodis then employed to estimate the targets' positions and velocities from therecovered target information matrices. Numerical experiments demonstrate thatthe proposed LiQuiD-MIMO radar, configured with the developed algorithm, canachieve accurate target parameter estimation.

LiQuiD-MIMO Radar: Distributed MIMO Radar with Low-Bit Quantization