Abstract
Resemblance coefficient (RC) feature extraction approach for radar emitter signals was proposed. Definition and properties of RC were given. Feature extraction algorithm based on RC was described in detail and the performances of RC features were also analyzed. Neural network classifiers were designed. Theoretical analysis results and simulation experiments of 9 typical radar emitter signal feature extraction and recognition show that RC features are not sensitive to noise and average accurate recognition rate rises to 99.33%, which indicates that the proposed approach is effective.
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© 2004 Springer-Verlag Berlin Heidelberg
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Zhang, G., Rong, H., Jin, W., Hu, L. (2004). Radar Emitter Signal Recognition Based on Resemblance Coefficient Features. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_83
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DOI: https://doi.org/10.1007/978-3-540-25929-9_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22117-3
Online ISBN: 978-3-540-25929-9
eBook Packages: Springer Book Archive