混响背景下低秩矩阵恢复的目标亮点特征提取

有源声呐探测水下目标时,混响干扰增加了从目标回波信号中提取目标亮点特征的难度.依据目标回波与混响在时频域上能量分布的相关性不同,采用自适应核时频分析方法将目标回波信号变换到时频域上进行分析.通过低秩矩阵恢复方法将目标回波与混响分到稀疏矩阵和低秩矩阵中,从而分离目标回波与混响,降低混响对回波信号的干扰.针对稀疏矩阵采用Hough变换提取回波中的亮点峰,得到目标的亮点特征。通过仿真和实验数据证明在较低信混比情况下通过低秩矩阵恢复方法能够在时频域上进一步区分目标回波与混响,达到抑制混响的目的,便于获取目标亮点特征。 

Extracting target highlight feature based on low-rank matrix recovery in reverberation background

When the active sonar detects the underwater target,the reverberation interference increases the difficulty of extracting the target bright spot feature from the target echo signal.According to the correlation between the target echo and the reverberation in the time-frequency domain,the adaptive-kernel function time-frequency analysis method is used to transform the target echo signal into the time-frequency domain.The target echo and reverberation are divided into the sparse matrix and the low rank matrix by the low rank matrix recovery method,thereby separating the target echo and the reverberation,and reducing the interference of the reverberation on the echo signal.The Hough transform is used to extract the bright peaks in the echoes for the sparse matrix,and the highlight features of the target are obtained.The simulation and actual experimental data prove that the low-rank matrix recovery method can further distinguish the target echo and reverberation in the time-frequency domain with low signal-to-mix ratio,so as to suppress reverberation and obtain the target bright spot features more easily.