Abstract
In this paper, a novel sparsity-aware direction of arrival (DOA) estimation scheme for a noncircular source is proposed in multiple-input multiple-output (MIMO) radar. In the proposed method, the reduced-dimensional transformation technique is adopted to eliminate the redundant elements. Then, exploiting the noncircularity of signals, a joint sparsity-aware scheme based on the reweighted norm penalty is formulated for DOA estimation, in which the diagonal elements of the weight matrix are the coefficients of the noncircular MUSIC-like (NC MUSIC-like) spectrum. Compared to the existing norm penalty-based methods, the proposed scheme provides higher angular resolution and better DOA estimation performance. Results from numerical experiments are used to show the effectiveness of our proposed method.
Highlights
Multiple-input multiple-output (MIMO) radar [1] has been presented as a novel sensor array configuration for several years, and the advantages of MIMO radar have been investigated in [2,3,4,5].In general, MIMO radar can be categorized into statistical MIMO radar [2] and colocated MIMO radar [3]
The contributions of the proposed method are summarized as follows: (i) utilize the reduced dimensional transformation matrix to eliminate the redundant elements in MIMO radar, the received data can be extended by utilizing the noncircularity of signals; (ii) formulate a weight matrix for enhancing the sparsity of the solution by using the multiple signal classification (MUSIC)-like spectrum; (iii) formulate a joint sparsity-aware scheme based on the reweighted l1 norm penalty for direction of arrival (DOA) estimation
Both transmit and receive antennas are arranged in half-wavelength-spaced uniform linear arrays (ULAs), i.e., dr = dt = λ/2, where dr and dt are the distance between adjacent sensors in the transmit and receive arrays, respectively, and λ is the wavelength
Summary
Multiple-input multiple-output (MIMO) radar [1] has been presented as a novel sensor array configuration for several years, and the advantages of MIMO radar have been investigated in [2,3,4,5]. The contributions of the proposed method are summarized as follows: (i) utilize the reduced dimensional transformation matrix to eliminate the redundant elements in MIMO radar, the received data can be extended by utilizing the noncircularity of signals; (ii) formulate a weight matrix for enhancing the sparsity of the solution by using the MUSIC-like spectrum; (iii) formulate a joint sparsity-aware scheme based on the reweighted l1 norm penalty for DOA estimation Due to using both the the noncircularity of signals and the reweighted l1 norm penalty to enhance the sparsity of the solution, the proposed scheme achieves better angle estimation performance and higher resolution than traditional l1 norm penalty-based methods. || · ||1 and || · || F are the l1 norm and Frobenius norm, respectively
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