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EXTRACTION AND ORGANIZATION OF METADATA FEATURE FOR UNDERWATER TARGET RECOGNITION BY SONAR ECHOES

机译:声纳回声的水下目标识别元数据特征的提取与组织

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摘要

To recognize an underwater target precisely is always a very difficult task for the navy due to the interference-filled under sea. Sonar is the most efficient way to detect items in the underwater world but the recognition still depends on sonarman. As well known, the feature extraction method is the key of automatic target recognition. In this paper, a model of 2-dimensional metadata of echo is defined, which is based on echo's frequency and temporal domain information. It contains two features, energy difference and zero cross rate. This paper concentrated on extraction of every feature and the organization method. Experiment results show the effectiveness of the presented approach.
机译:由于填充干涉,识别水下目标始终是海军的一项非常艰巨的任务。声纳是检测水下世界中的物品的最有效方式,但识别仍然取决于Sonarman。众所周知,特征提取方法是自动目标识别的关键。在本文中,定义了回波的二维元数据模型,其基于回波的频率和时间域信息。它包含两个特征,能量差和零交叉速率。本文集中在各个特征和组织方法的提取。实验结果表明了提出的方法的有效性。

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