Abstract
Modern aircraft and ships are equipped with radars emitting specific patterns of electromagnetic signals. The radar antennas are detecting these patterns which are required to identify the types of emitters. A conventional way of emitter identification is to categorize the radar patterns according to the sequences of frequencies, time of arrivals, and pulse widths of emitting signals by human experts. In this respect, this paper presents a method of classifying the radar patterns automatically using the network of calculating the p-values of testing the hypotheses of the types of emitters referred to as the class probability output network (CPON). Through the simulation for radar pattern classification, the effectiveness of the proposed approach has been demonstrated.
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References
Schleher, D.: Introduction to Electronic Warfare. Artech House, New York (1986)
Vapnik, V.: Statistical Learning Theory. Wiley, New York (1998)
Park, W., Kil, R.: Pattern classification with class probability output network. IEEE Trans. Neural Netw. 20(10), 1659–1673 (2009)
Rosas, H., Kil, R., Han, S.: Automatic media data rating based on class probability output networks. IEEE Trans. Cons. Electron. 56(4), 2296–2302 (2010)
AbouRizk, S., Halpin, D., Wilson, J.: Fitting beta distributions based on sample data. J. Constr. Eng. Manag. 120(2), 288–305 (1994)
Rohatgi, V., Saleh, A.: Nonparametric statistical inference. In: An Introduction to Probability and Statistics, 2nd edn. Wiley, New York (2001)
Kohonen, T.: Improved versions of learning vector quantization. In: IEEE International Joint Conference on Neural Networks, vol. 1, pp. 545–550 (1990)
Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011)
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© 2015 Springer International Publishing Switzerland
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Kim, L.S., Kil, R.M., Jo, C.H. (2015). Radar Pattern Classification Based on Class Probability Output Networks. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9489. Springer, Cham. https://doi.org/10.1007/978-3-319-26532-2_53
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DOI: https://doi.org/10.1007/978-3-319-26532-2_53
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