论文标题
通过矩阵完成抑制海洋混响，传感器故障
Ocean Reverberation Suppression via Matrix Completion with Sensor Failure
论文作者
论文摘要
在海洋环境中，混响是一种常见且强烈的干扰，可显着降低目标轴承估计的性能。同时，由于水下场景很复杂，在实际声纳部署中，传感器故障是不可避免的。因此，对于传感器故障而在海洋混响中进行目标检测是一个挑战。为了解决这个问题，我们提出了一种基于本文中矩阵等级特征低等级特征的原则的改进方法。首先，我们利用Hankel结构化矩阵来抵消传感器故障的问题。然后，利用基于L1-Norm和L2-Norm的矩阵完成算法（MC）从损坏的接收到的矩阵中恢复真实的信号矩阵。数值结果表明，与其他相关方法相比，L1-norm在恢复概率方面提供了更好的能力，并显示了具有狭窄的梁宽度和低侧孔的轴承估计的最佳鲁棒性。此外，提出的方法验证了混响抑制的性能，并实现了目标检测的高分辨率。
In the ocean environment, reverberation is a common and strong interference which significantly degrades the performance of target bearing estimation. Meanwhile, sensor failure is inevitable in actual sonar deployment as the underwater scene is complicated. Therefore, it is a challenge for target detection in the ocean reverberation with sensor failure. To address this issue, we propose an improved approach based on the principle of low rank characteristics of matrix in this paper. Firstly, we utilize Hankel structured matrix to counteract the problem of sensor failure. Then, the algorithm of matrix completion (MC) based on l1-norm and l2-norm are exploited to recover the true signal matrix from the corrupted received matrix. Numerical results demonstrate that compared with other related methods, the l1-norm provides better capability in the probability of recovery and shows the best robustness of bearing estimation with the narrow beam width and low sidelobe. Moreover, the proposed approach verifies the performances of reverberation suppression and achieves high resolution of target detection.
