Radar emitter signal recognition based on feature selection algorithm

Authors:
Gexiang Zhang;Laizhao Hu;Weidong Jin
Affiliations:
National EW Laboratory, Chengdu, Sichuan, China;National EW Laboratory, Chengdu, Sichuan, China;School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
Venue:
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Year:
2004

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Abstract

Rough set theory (RST) was introduced into radar emitter signal (RES) recognition A novel approach was proposed to discretize continuous interval valued features and attribute reduction method was used to select the best feature subset from original feature set Also, rough neural network (NN) classifier was designed Experimental results show that the proposed hybrid approach based on RST and NN achieves very high recognition rate and good efficiency It is proved to be a valid and practical approach.