Extraction and Organization of Metadata Feature for Underwater Target Recognition by Sonar Echoes

Author

Gan, Ya-li ; Yuan, Jian ; LI, Guo-hui

Author_Institution

Dept. of Syst. Eng., Nat. Univ. of Defense Technol., Changsha

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

3317

Lastpage

3322

Abstract

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

Keywords

echo; feature extraction; learning (artificial intelligence); meta data; object recognition; sonar signal processing; sonar target recognition; sonar tracking; target tracking; machine learning; metadata feature extraction; metadata feature organization; navy; signal processing; sonar echo; sonar fingerprint; temporal domain information; underwater target recognition; Cybernetics; Data mining; Feature extraction; Fingerprint recognition; Frequency; Machine learning; Management training; Pattern recognition; Sonar detection; Target recognition; Underwater tracking; Sonar fingerprint; feature extraction; machine learning; signal processing; underwater target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258467

Filename

4028640