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改进次最佳检测在侧扫声呐底混响抑制中的应用*
引用本文:马龙双,许枫,刘佳,蒋立军.改进次最佳检测在侧扫声呐底混响抑制中的应用*[J].应用声学,2021,40(1):147-148.
作者姓名:马龙双  许枫  刘佳  蒋立军
作者单位:中国科学院声学研究所,中国科学院声学研究所,中国科学院声学研究所,中国科学院声学研究所
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:侧扫声呐进行沉底小目标探测时,底混响是主要背景干扰。底混响通常是一种非平稳、非高斯的带限噪声,它使得白噪声条件下的滤波器性能受到限制。在混响背景下常利用自回归模型对接收信号进预行白化处理,但对于实际侧扫声呐应用,白化后直接匹配滤波的处理效果不甚理想。针对此问题,在自回归模型预白化的基础上,提出采用一种次最佳检测与多分辨二分奇异值分解相结合的改进方法。该方法首先对接收信号进行分段处理,利用改进Burg算法估计每段数据自回归模型的系数及阶数;然后构造白化滤波器对分段数据预白化,并对白化后的数据进行多分辨二分奇异值分解;最后应用ostu方法对原始声图和处理后的声图进行目标检测。仿真与实验结果表明,该方法明显提高了信混比,改善了侧扫声呐沉底静态小目标的成图质量,有利于后期实现基于图像的目标自动检测。

关 键 词:侧扫声呐  底混响  自回归模型  多分辨二分奇异值分解
收稿时间:2020/4/26 0:00:00
修稿时间:2020/12/31 0:00:00

Application of improved sub-optimal detection in the side-scan sonar bottom reverberation suppression
Institution:Institute of Acoustics,Chinese Academy of Sciences,Institute of Acoustics, Chinese Academy of Sciences,Institute of Acoustics, Chinese Academy of Sciences,Institute of Acoustics, Chinese Academy of Sciences
Abstract:Bottom reverberation is the main background interference of side-scan sonar target detection. It is often considered as a kind of non-stationary colored noise, which degrades the performance of the matched filter that is the optimum detector in white background noise.The received signals are used to be pre-whitened with the Auto-Regressive(AR)model in reverberation background,however,in actual side-scan sonar applications,the result is not satisfying under the background of strong reverberation.In order to solve the problem, based on the pre-whitening of the AR model, an improved method combining sub-optimal detection with multi-resolution binary singular value decomposition (MBSVD) is proposed.The algorithm contains three steps, constructing a whitening filter by AR model to pre-whitening the bottom reverberation,then performing multi-resolution binary singular value decomposition on the whitened data.Finally,the original image and processed acoustic image are processed by the ostu method.The simulation and experiment results show that the proposed method can improve the signal-to-reverberation ratio and the acoustic image quality of side-scan sonar.
Keywords:Side-scan sonar  Bottom reverberation  Auto-Regressive model  Multi-resolution binary singular value decomposition
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