DocumentCode :
2295945
Title :
A fuzzy pattern recognition method of radar signal based on neural network
Author :
Ting Chen ; Wei Chen
Author_Institution :
Unmanned Aircraft Vehicle Teaching & Res. Sect., A A P.L.A., Hefei, China
Volume :
3
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1178
Lastpage :
1181
Abstract :
Radar signal recognition is an important step of radar countermeasure processing. The classical recognition method is called weight distance, in which the feature parameter weights are obtained by expert and then the weight distance of unknown radar signal and signal template in database is computed. For it existing subjectivity in setting of feature parameter weights with classical recognition method, and the computing method of recognition is too simple, all of which make recognition result can´t reflect the true fact objectively. Considering this point, a fuzzy pattern recognition method based on neural network getting weights to radar signal recognition is studied in this paper, the feature parameter weights in this method are fixed on by neural network and then the unknown radar signal is recognized by fuzzy pattern recognition method. Simulation experiment and its result show the method in this paper is practicable and more reliable compared with classical method.
Keywords :
electronic countermeasures; fuzzy set theory; neural nets; radar computing; radar signal processing; radar target recognition; database; feature parameter weights; fuzzy pattern recognition method; neural network; radar countermeasure processing; radar signal recognition; signal template; weight distance; Artificial neural networks; Databases; Feature extraction; Pattern recognition; Radar countermeasures; Target recognition; Neural Network; feature parameter; fuzzy pattern recognition; membership function; weight value;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5583660
Filename :
5583660
Link To Document :
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