The Multistage Filtering Method of Cavity Sonar Signal
Zeng Xin, Cao Xue-Shen*, Li Chao, Wang Yao-Xin, Zhao Jia-Heng, Chen Hao
1. Institute of Acoustics,Chinese Academy of Sciences, Beijing 100190, China.
2. University of Chinese Academy of Sciences, Beijing 100049, China.
3. Beijing Engineering Research Center for Deep Drilling Exploration, Beijing 100190, China.
4. National Petroleum and Natural Gas Pipeline Network Group Energy Storage Technology Co.,Ltd, Shanghai 200011, China.
Abstract：
A multistage filtering strategy was proposed to target the periodic noise present in the cavity sonar signal of salt cavern gas storage. First, the relevant signal's frequency band range is selected, and the parameters of the signal's time-frequency domain are collected using the Short-Time Fourier Transform (STFT). Second, the adaptive Wiener filter is adjusted with windows of variable lengths, completing the fi rst stage of filtering. Lastly, the second stage involves utilizing the wavelet transform to enhance the capacity for filtering periodic noise. The Signal-to-Noise Ratio (SNR) and correlation coefficient are thoroughly estimated to assess the sonar signal after the second stage of filtering, and the Minimum Mean Squared Error (MMSE) is employed to evaluate the impact of the first filtering stage, confirming the effectiveness of the proposed filtering technique. According to various experiments, the method presented in this work effectively suppresses multiple types of noise, improves the accuracy of echo extraction, and enhances the SNR by approximately 10 dB, all while preserving the characteristics of the original signal.
作者简介: Zeng Xin, is a PhD student in Acoustics at the Institute of Acoustics, Chinese Academy of Sciences, Beijing, China. Her research interests are the noise reduction processing of sonar signals and the design of phased array circuits.
2025, Vol. 22 
