Issue |
MATEC Web Conf.
Volume 283, 2019
The 2nd Franco-Chinese Acoustic Conference (FCAC 2018)
|
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Article Number | 03006 | |
Number of page(s) | 5 | |
Section | Acoustic and Elastic Wave Scattering | |
DOI | https://doi.org/10.1051/matecconf/201928303006 | |
Published online | 28 June 2019 |
Robust adaptive beamforming method for active sonar in single snapshot
Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Hangzhou, China
* Corresponding author: 1513638732@qq.com
Forming narrow beams is a useful way for active sonar to anti-reverberation when it works in the shallow water. High-resolution adaptive beamforming with the performance of narrow beamwidths and low sidelobe levels is a better and more efficient method, particularly in the scenario where the installation space for sonar array is limited, such as hull-mounted sonar. Due to the short duration of target echo signal in the complex and varying acoustic channel, conventional adaptive beamforming methods are invalid. Therefore, this paper proposes a robust adaptive beamforming method for active sonar in single snapshot, also called the steered dominant mode rejection (STDMR). Firstly, STDMR steered the sample covariance matrix (STCM) based on wide-band focusing, which the needed number of snapshots is greatly reduced. Secondly, by partial eigendecomposition, the large eigenvalues of the STCM which are greater than the noise energy and their eigenvectors are used for dominant mode rejection (DMR). DMR is a typical eigenspace-based algorithm which has small computational load and fast convergence speed. Finally, modified with the methods of diagonal loading of 3-5dB over the noise energy and signal mismatch protection, improved the robustness of this method. Simulation and experimental data analysis shows that the STDMR method achieves narrow beams and low-level sidelobes in single snapshot. Hence, the STDMR beamformer is an appropriate implementation to use for active sonar detection systems.
© The Authors, published by EDP Sciences, 2019
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