Issue |
MATEC Web Conf.
Volume 283, 2019
The 2nd Franco-Chinese Acoustic Conference (FCAC 2018)
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Article Number | 07010 | |
Number of page(s) | 7 | |
Section | Ultrasounds, Signal Processing, and NDT/E | |
DOI | https://doi.org/10.1051/matecconf/201928307010 | |
Published online | 28 June 2019 |
Research on reverberation characteristics analysis and suppression methods for active continuous detection
Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Hangzhou City, Zhejiang Province, China
* Corresponding author: skl_chent@163.com
Compared with the traditional active detection with monopulse periodic emission mode, active continuous detection has the advantages of large emission duty ratio and continuous acquisition of process information. It can effectively overcome the disadvantages of high false alarm probability, poor environment adaptation ability and low detection efficiency in traditional active detection, so then improving the system detection ability. But active continuous detection is also facing more serious reverberation. In order to further improve capacity, the adaptable reverberation characteristics and detection methods are carried out in this paper. On the basis of theoretical modelling, the relationship between the characteristics of the active continuous detection reverberation and the signal form, the hydrological environment and the emission power are studied. The time frequency characteristics of reverberation and the attenuation law with distance of reverberation are mastered. A reverberation suppression method based on adaptive beamforming of sub-band steered minimum variance algorithm (SSMV) is studied for active continuous detection. Considering signal bandwidth and fast convergence, etc. The relationship between sub-array partition and reverberation suppression ability is analyzed. The validity of reverberation characteristic analysis is verified by simulation, the performance of the method of reverberation suppression is verified by sea trial data processing.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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