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• W4386446912 abstract "Estimation of the two-dimensional (2D) direction of arrival (DOA) is important for various signal processing and wireless communication applications. While off-grid compressed sensing has shown advantages in DOA estimation for the uniform linear array (ULA), it encounters difficulties when applied to the 2D array such as a uniform plane array (UPA) due to the exploded size of the observation matrix in compressed sensing. To deal with the 2D off-grid DOA estimation problem, this paper proposes a structured sparse Bayesian learning method, which exploits the joint sparsity among different snapshots, and the joint sparsity between the grid component and the bias. A grid-redefined method is further adopted to deal with the model error raised by the Taylor approximation. Numerical simulations show that the proposed algorithm has improved accuracy in comparison to different competing DOA estimation methods." @default.
• W4386446912 created "2023-09-06" @default.
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• W4386446912 date "2023-08-10" @default.
• W4386446912 modified "2023-09-27" @default.
• W4386446912 title "Off-grid DOA Estimation on Uniform Plane Array Based on Structured Sparse Bayesian Learning" @default.
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• W4386446912 doi "https://doi.org/10.1109/iccc57788.2023.10233448" @default.
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