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High-resolution angle-Doppler imaging by sparse recovery of underwater acoustic signals(2020 No.2)
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Title: High-resolution angle-Doppler imaging by sparse recovery of underwater acoustic signals


Author(s): KOU Siwei; FENG Xi'an; BI Yang; HUANG Hui;


Affiliation(s): School of Marine Science and Technology, Northwestern Polytechnical University


Abstract: The low resolution of Fourier two-dimensional spatial temporal spectrum estimation and the insufficient sample size of sonar space time sampling data often caused difficulties in high-resolution space time spectrum estimation. Aiming to solve this problem, we proposed a high-resolution angle-Doppler imaging method and designed an anti-reverberation space time filter based on the sparse recovery of underwater acoustic signals. The proposed imaging method established the spatial temporal sparse representation model of array signal under the condition of few observation samples of single measurement vector (SMV), and reconstructed the high-resolution angle-Doppler profile of echo and reverberation through the matching pursuit(MP) algorithm and basis pursuit(BP) algorithm. By utilizing the space time distribution characteristics of echo and reverberation and the prior information of sonar rangecell under test (RUT), a reverberation dictionary composed of special space time guidance vectors was designed, and was used to reconstruct the reverberation and formed an anti-reverberation space time filter to suppress the reverberation interference of angle-Doppler plane. Computer simulations indicated that, under two conditions of forward and side-view array of moving sonar, the single measurement vector of sonar array was successfully used in the reverberation background to reconstruct the high-resolution angle-Doppler profile of low-speed moving target multi-spot echo. Its frequency resolution had a better performance than the Fourier resolution and the angle resolution broke through the Rayleigh limit of the array, the resolution was obviously superior to the Fourier space time spectrum estimation.


 
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