Direct Position Determination of Coherently Distributed Noncircular Sources

Lu, Zhiyu; Wang, Jianhui; Ba, Bin; Wang, Da-Ming

doi:10.1155/2018/4517393

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Two-dimensional-DOA estimation has been widely used because it can better describe the spatial characteristics of the target. Lu et al [35] proposed a 2D-DOA estimation algorithm based on the symmetric rotation invariable relation of non-circular signal characteristics, which is able to directly estimate the target position by constructing an objective function integrating the information of multiple observation stations without relying on the distribution model. Z. Zheng et al [36] proposed a 2D-DOA estimation algorithm based on a double parallel line array combining rotation invariance and propagation operator method.…”

Section: Introductionmentioning

confidence: 99%

A 2D-DOA Sparse Estimation Method with Total Variation Regularization for Spatially Extended Sources

Liu,

Liu

et al. 2023

Applied Sciences

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In this paper, a novel two-dimensional direction of arrival (2D-DOA) estimation method with total variation regularization is proposed to deal with the problem of sparse DOA estimation for spatially extended sources. In a general sparse framework, the sparse 2D-DOA estimation problem is formulated with the regularization of extended source characteristics including spatial position grouping, acoustic signal block sparse, and correlation features. An extended sources acoustic model, two-dimensional array manifold and its complete representation, total variation regularization penalty term, and the regularization equation are built, and are utilized to seek the solutions where the non-zero coefficients are grouped together with optimum sparseness. A total variation sparse 2D-DOA estimation model is constructed by combining total variation regularization with LASSO. The model can be easily solved by the convex optimization algorithm, and the solving process can promote the sparsity of the solution on the spatial derivatives and the solution itself. The theoretical analysis results show that the steps of decorrelation processing and angle matching of traditional 2D-DOA estimation methods could be avoided when adopting the proposed method. The proposed method has better robustness to noise, better sparsity, and faster estimation speed with higher resolution than traditional methods. It is promising to provide a coherent sources sparse representation of a non-strictly sparse field.

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Section: Introductionmentioning

confidence: 99%