In this paper, we present a compressed sensing method for complex-valued signals based on multiple measurement vector compressed sensing model. The proposed method constrains the real and imaginary parts of the recovered signal to have the same sparsity profile. It is applied to a compressed sensing through-the-wall radar imaging problem. Experiments based on synthetic data shows that the proposed method achieves lower reconstruction error than the existing CS method.
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