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An alternative hybrid time–frequency domain approach based on the fast iterative shrinkage-thresholding algorithm (FISTA) is presented for rotating acoustic source identification. This approach is similar to the existing approaches based on the deconvolution approach for the mapping of acoustic sources (DAMAS) and non-negative least squares (NNLS) without the sample interpolation of sound pressure signal in the time domain. The acoustic source is first identified using the time-domain tracking Delay and Sum (DAS) method. The Frequency-domain deconvolution is then performed to attenuate the sidelobes and improve the spatial resolution. The simulation and experimental results indicate that the proposed approach is robust to the sampling rate and enjoys the good spatial convergence and resolution, effective sidelobe suppression, accurate quantification, as well as high computational efficiency. In general, at a low time-domain sampling rate, the proposed approach outperforms the DAMAS- or NNLS-based hybrid time–frequency domain approaches without the sample interpolation of sound pressure signal in the time domain.

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An Alternative Hybrid Time-Frequency Domain Approach Based on Fast Iterative Shrinkage-Thresholding Algorithm for Rotating Acoustic Source Identification