利用主动声纳数据进行盲信号分离和混响消除

F. Cong, Yifan Hu, Xizhi Shi, Chi Hau Chen, Liangji Lin
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引用次数: 4

摘要

利用已有的先验知识,我们探索了一种将主动声纳数据分离为混响和运动目标回波的混响抑制新方法。从信号处理的角度来看,如下所述的方法是基于主动声纳数据属性和混响如何形成的过程。假设主动声呐数据可分为目标回波信号和混响信号两部分。首先,从主动声纳数据中生成一个反向矩阵来近似经典的盲信号分离模型。其次,对后向矩阵进行盲信号分离后,进行分离。第三,选取峰度最大的估计信号作为期望目标回波信号,同时消除混响。第四,人的听觉特征有助于过程的适应性。实际的海上实验证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind signal separation and reverberation cancelling with active sonar data
With easily available prior knowledge, we explore a new approach for nulling of reverberation through separating active sonar data into reverberation and moving target echo. From the perspective of signal processing, the method, as outlined below, is based on active sonar data properties and the process of how reverberation is formulated. It is assumed that active sonar data can be separated into two parts that are target echo signal and reverberation. First, we generate a backward matrix from active sonar data to approximate the classical blind signal separation model. Second, after blind signal separation is performed on the backward matrix, separation is done. Third, the estimated signal with the largest kurtosis is selected as the desired target echo signal and the reverberation is cancelled at the same time. Fourth, the human hearing feature helps the process to be adaptive. The real sea experiment proves the method to be effective.
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