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http://dx.doi.org/10.9717/kmms.2015.18.1.009

Signal Synthesis and Feature Extraction for Active Sonar Target Classification  

Uh, Y. (Dept. of Information & Communication, Changwon National University)
Seok, J.W. (Dept. of Information & Communication, Changwon National University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.1, 2015 , pp. 9-16 More about this Journal
Abstract
Various approaches to process active sonar signals are under study, but there are many problems to be considered. The sonar signals are distorted by the underwater environment, and the spatio-temporal and spectral characteristics of active sonar signals change in accordance with the aspect of the target even though they come from the same one. And it has difficulties in collecting actual underwater data. In this paper, we synthesized active target echoes based on ray tracing algorithm using target model having 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to synthesized target echoes to extract feature vector. Recognition experiment was performed using probabilistic neural network classifier.
Keywords
Active Sonar; Target Classification; Fractional Fourier Transform; Probabilistic Neural Network;
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