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

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 echos 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.

关键词： Sonar fingerprint underwater target recognition feature extraction signal processing machine learning

作者: YA-LI GAN JIAN YUAN GUO-HUI LI

作者单位: Information Integration & Training Simulation Lab, Department of System Engineering, School of Information System & Management, National University of Defense Technology, Changsha 410073, Hunan, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3317-3322

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）