摘要
底混响是侧扫声呐进行沉底静态小目标探测时的主要背景干扰,针对此问题提出了一种基于多级二分奇异值分解BSVD子空间投影的底混响抑制方法。该方法首先对接收信号构造二阶Hankel矩阵,通过矩阵的奇异值确定混响子空间,然后利用正交子空间投影抑制回波信号中的底混响,最后根据所选级数对回波信号进行多级正交子空间投影,并用otsu方法对原始声图和处理后的声图进行目标检测。实验结果表明,该方法改善了侧扫声呐沉底静态小目标的成图质量,更利于后期实现基于图像的目标自动检测。
Bottom reverberation is the main background interference of side-scan sonar small static target detection.To suppress bottom reverberation and improve target detection and recognition performance,an multi-binary singular value based on subspace projection is proposed.The algorithm contains three steps,constructing second-order Hankel matrix with the side-scan sonar signal and performing binary singular value decomposition.Then,orthogonal subspace projection are used to mitigate bottom reverberation and make target signals prominent.Finally,performing multi-binary singular value decomposition,which choosing decomposition order by the selected,and processing the image by the otsu method.The experiment results show that the proposed method can improve the signal-to-reverberation ratio and the acoustic image quality of side-scan sonar.
作者
马龙双
许枫
刘佳
蒋立军
MA Longshuang;XU Feng;LIU Jia;JIANG Lijun(Chinese Academy of Sciences Ocean Acoustic Technology Center,Institute of Acoustics,Chinese Academy of Sciences,Beijing,100190,China;University of Chinese Academy of Sciences,Beijing,100049,China)
出处
《网络新媒体技术》
2021年第3期51-57,共7页
Network New Media Technology
基金
国家自然科学基金资助项目(编号:11404365)
国家自然科学基金项目(编号:61801470)
中国科学院声学研究所“青年英才计划”(编号:QNYC201730)共同资助。
关键词
侧扫声呐
底混响
多级二分奇异值分解
子空间投影
side-scan sonar
bottom reverberation
multi-binary singular value decomposition
subspace projection
