Abstract
In this paper, we develop a robust direction-of-arrival (DOA) estimation algorithm with a nested array with unknown mutual coupling. By using the matrix transformation of the product of mutual coupling matrix and steering vector, we firstly derive a coarray signal model including a manifold matrix without mutual coupling effect. Subsequently, we build the block sparse representation of the coarray signal by exploiting the sparsity of the signals. Finally, we estimate the DOAs of sources by formulating a simplified block sparse recovery problem. The proposed algorithm utilizes all coarray outputs and reduces the influence of mutual coupling effect, and thus can resolve more sources than the number of sensors. Numerical results demonstrate the superiority of the proposed algorithm over several existing techniques.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China under Grant 62171089, by the Natural Science Foundation of Sichuan Province under Grant 2022NSFSC0497, by the Sichuan Science and Technology Program under Grant 2022YFG0162, by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515011163, and by the Shenzhen Science and Technology Program under Grant JCYJ20210324143004012.
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Xu, Y., Zheng, Z. & Wang, WQ. Block Sparse Recovery Approach for DOA Estimation in Nested Array with Unknown Mutual Coupling. Circuits Syst Signal Process 42, 5079–5090 (2023). https://doi.org/10.1007/s00034-023-02351-0
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DOI: https://doi.org/10.1007/s00034-023-02351-0