Abstract
In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to double the virtual array aperture, and the real-valued data are obtained by utilizing unitary transformation. Then a real-valued block sparse model is established based on a novel over-complete dictionary, and a UNNM algorithm is formulated for recovering the block-sparse matrix. In addition, the real-valued NC-MUSIC spectrum is used to design a weight matrix for reweighting the nuclear norm minimization to achieve the enhanced sparsity of solutions. Finally, the DOA is estimated by searching the non-zero blocks of the recovered matrix. Because of using the noncircular properties of signals to extend the virtual array aperture and an additional real structure to suppress the noise, the proposed method provides better performance compared with the conventional sparse recovery based algorithms. Furthermore, the proposed method can handle the case of underdetermined DOA estimation. Simulation results show the effectiveness and advantages of the proposed method.
Highlights
The parameter estimation problem has attracted more and more attentions in multiple input multiple output (MIMO) radar [1,2,3,4], especially for direction of arrival (DOA) estimation
For MIMO radar, some subspace-based methods are extended for DOA estimation by using the noncircular property of signals, and the theoretical analysis and simulation results verify that these methods achieve higher spatial resolution and better performance than traditional subspace-based methods [23,24,25]
We have proposed a unitary nuclear norm minimization algorithm for DOA
Summary
The parameter estimation problem has attracted more and more attentions in multiple input multiple output (MIMO) radar [1,2,3,4], especially for DOA estimation. For MIMO radar, some subspace-based methods are extended for DOA estimation by using the noncircular property of signals, and the theoretical analysis and simulation results verify that these methods achieve higher spatial resolution and better performance than traditional subspace-based methods [23,24,25]. In [27], a nuclear norm minimization (NNM) framework is proposed to effectively use the whole aperture corresponding to the extended data It provides better angle estimation performance than the SR-based method in [28]. A novel unitary nuclear norm minimization (UNNM) algorithm is proposed for DOA estimation of noncircular sources in MIMO radar. Denotes the diagonal matrix, and blkdiag{A, B} represents a block diagonal matrix with diagonal entries A and B. det{A} is the determinant of the square matrix A, and || · || F denotes the Frobenius norm
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