Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival
(DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with
unknown mutual coupling is considered, and a tensor-based angle estimation method is
proposed. In the proposed method, making use of the banded symmetric Toeplitz structure
of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in
the tensor domain. Then, a special enhancement tensor is formulated to capture both the …
(DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with
unknown mutual coupling is considered, and a tensor-based angle estimation method is
proposed. In the proposed method, making use of the banded symmetric Toeplitz structure
of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in
the tensor domain. Then, a special enhancement tensor is formulated to capture both the …
In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method, making use of the banded symmetric Toeplitz structure of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in the tensor domain. Then, a special enhancement tensor is formulated to capture both the noncircularity and inherent multidimensional structure of strictly noncircular signals. After that, the higher-order singular value decomposition (HOSVD) technology is applied for estimating the tensor-based signal subspace. Finally, the direction-of-departure (DOD) and direction-of-arrival (DOA) estimation is obtained by utilizing the rotational invariance technique. Due to the use of both noncircularity and multidimensional structure of the detected signal, the algorithm in this paper has better angle estimation performance than other subspace-based algorithms. The experiment results verify that the method proposed has better angle estimation performance.
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