In this paper, a reweighted sparse representation algorithm based on noncircular sources\nis proposed, and the problem of the direction of arrival (DOA) estimation for multiple-input\nmultiple-output (MIMO) radar with mutual coupling is addressed. Making full use of the special\nstructure of banded symmetric Toeplitz mutual coupling matrices (MCM), the proposed algorithm\nfirstly eliminates the effect of mutual coupling by linear transformation. Then, a reduced dimensional\ntransformation is exploited to reduce the computational complexity of the proposed algorithm.\nFurthermore, by utilizing the noncircular feature of signals, the new extended received data matrix is\nformulated to enlarge the array aperture. Finally, based on the new received data, a reweighted matrix\nis constructed, and the proposed method further designs the joint reweighted sparse representation\nscheme to achieve the DOA estimation by solving the l1-norm constraint minimization problem.\nThe proposed method enlarges the array aperture due to the application of signal noncircularity,\nand in the presence of mutual coupling, the proposed algorithm provides higher resolution and\nbetter angle estimation performance than ESPRIT-like, l1-SVD and l1-SRDML (sparse representation\ndeterministic maximum likelihood) algorithms. Numerical experiment results verify the effectiveness\nand advantages of the proposed method.
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