DOA Estimation of Shifted Coprime Array Based on Covariance Matrix Reconstruction
Authors: 
Wei Yang, Dongming Xu, Jiaqi XueAuthors Info & Claims
Wei Yang, Dongming Xu, Jiaqi XueAuthors Info & ClaimsPages 900 - 904
Abstract
Aiming at the problem that the maximum number of continuous uniform array elements of the virtual array extended by the coprime array algorithm is small and the degree of freedom is still low. A matrix reconstruction DOA estimation algorithm based on virtual array interpolation is proposed. Firstly, the general coprime array is improved by optimizing the array layout to form a new array, and the new array is derived from a non-uniform virtual array, which increases the number of array elements and improves the degree of freedom; secondly, the idea of virtual array interpolation is used to fill the holes in the virtual domain A uniform linear virtual array is constructed, and finally the DOA is estimated by optimizing the design through atomic norm minimization and sparse reconstruction of the covariance matrix. The algorithm improves the degree of freedom of the array and makes full use of the information in the virtual array. The simulation results show the effectiveness of the new array algorithm.
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Index Terms
- DOA Estimation of Shifted Coprime Array Based on Covariance Matrix Reconstruction
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September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
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Published: 16 May 2023
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AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
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