Abstract
Beamforming is one of the most important techniques for multibeam echo sounder (MBES) for engineering applications, such as seafloor topographic survey and underwater target detection. However, due to the Rayleigh limit in the conventional beamforming (CBF) algorithm, the output of the beamforming is often limited by the aperture and the number of elements, thus leading to low resolution and signal-to-noise ratio (SNR). To further improve the resolution and array gain (AG) of the beamforming algorithm for MBES, a dynamic background suppression deconvolved multiple signal classification (DBSD–MUSIC) algorithm is proposed in this work. The dynamic variable point scattering function (PSF) is constructed using the signal characteristics of the signal covariance matrix for each moment. The MUSIC azimuth spectrum is deconvolved using the dynamic PSF and Richardson–Lucy (R–L) iterative algorithm. Thus, the azimuth spectrum of DBSD–MUSIC algorithm is obtained. Based on the analysis and comparison of the simulation results and experimental multibeam data, we show that the resolution of the proposed algorithm is better than the traditional MUSIC algorithm. In addition, it also has a better AG and the direction of arrival (DOA) estimation performance.
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Data available on request from the authors.
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Funding
This study was funded by the Jiaqi Wang: the Hainan provincial Joint Project of Sanya Yazhou Bay Science and Technology City, (620LH036), Haisen Li: Key-Area Research and Development Program of Guangdong Province, (2020B1111010002), Haisen Li: Fundamental Research Funds for the Central Universities, (3072021CFT0502).
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Li, H., Wang, J., Zhu, J. et al. Dynamic background suppression deconvolved high-resolution beamforming algorithm for the multibeam echo sounder. J Mar Sci Technol 28, 341–350 (2023). https://doi.org/10.1007/s00773-023-00923-y
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DOI: https://doi.org/10.1007/s00773-023-00923-y