LiQuiD-MIMO Radar: Distributed MIMO Radar with Low-Bit Quantization
Yikun Xiang (Nanjing University of Science and Technology); Feng Xi (Nanjing University of Science and Technology); Shengyao Chen (Nanjing University of Science and Technology)
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Distributed MIMO radar is known to achieve superior sensing performance by employing widely separated antennas.
However, it is challenging to implement a low-complexity distributed MIMO radar due to the complex operations at both the receivers and the fusion center.
This work proposes a low-bit quantized distributed MIMO (LiQuiD-MIMO) radar to significantly reduce the burden of signal acquisition and data transmission.
In the LiQuiD-MIMO radar, the widely-separated receivers are restricted to operating with low-resolution ADCs and deliver the low-bit quantized data to the fusion center. At the fusion center, the induced quantization distortion is explicitly compensated via digital processing. By exploiting the inherent structure of our problem, a quantized version of the robust principal component analysis (RPCA) problem is formulated to simultaneously recover the low-rank target information matrices as well as the sparse data transmission errors.
The least squares-based method is then employed to estimate the targets' positions and velocities from the recovered target information matrices.
Numerical experiments demonstrate that the proposed LiQuiD-MIMO radar, configured with the developed algorithm, can achieve accurate target parameter estimation.