Abstract
To recognize an underwater target precisely is always a more difficult task for the navy compared to the air force due to the complicated watery environment which is very different from the aerial circumstance. Part of the reason is that there is much more interference under the sea. Sonar is the most efficient way to detect items in the underwater world at the present time. In this paper, a genetic-based classifier system is designed which recognizes targets by sonar fingerprints. This method will, to a certain degree, relieve the sonar man of some of his work. Experiments show that the system gains acceptable speed and accuracy in the classifying operation. The proposed underwater target classifier system is highly automatic, with quite finite hardware requirements for operation.
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© 2006 Springer-Verlag Berlin Heidelberg
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Yuan, J., Li, GH. (2006). Underwater Target Recognition with Sonar Fingerprint. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_103
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DOI: https://doi.org/10.1007/11739685_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
Online ISBN: 978-3-540-33585-6
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