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- W4206090130 abstract "The core of compressed sensing (CS) is to recover a set of sparse signals from incomplete measurements. In this paper, to solve the coherent direction-of-arrival (DOA) estimation problem, it is formulated as a joint-sparse recovery problem by exploiting the signal sparsity in the spatial domain. When the sparsity level of the signals satisfies certain conditions, the signals are recoverable even in the case of coherent sources. By further considering the structure of the sparse signals, a more general condition for the recoverability is theoretically derived. Then a method is proposed based on the CS theory and the generalized MUSIC criterion. This criterion improves on MUSIC so that the support is reliably recovered under the case of rank-defect. In our method, we modify the criterion to make it applicable for continuous dictionaries. When the partial DOAs has been estimated, the modified criterion can estimate the remaining DOAs with higher accuracy. By alternately using the modified criterion, the proposed method achieves super-resolution. Simulation results demonstrate that the proposed method has satisfactory performance even in the case of coherent sources." @default.
- W4206090130 created "2022-01-26" @default.
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- W4206090130 date "2022-04-01" @default.
- W4206090130 modified "2023-10-14" @default.
- W4206090130 title "Joint sparse recovery for direction of arrival based on the generalized MUSIC criterion" @default.
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- W4206090130 doi "https://doi.org/10.1016/j.dsp.2021.103382" @default.
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