Emitter Signal Modulation Feature Recognition Based on Fisher Discrimination Dictionary Learning

doi:10.3969/j.issn.1000-1093.2018.03.017

Abstract

Abstract: The limited forms of atoms in analytical dictionary lead to sub-optimal matching of atoms and complex emitter signal, resulting in low recognition rate of signal modulation. A dictionary learning method based on Fisher discrimination criterion is proposed to improve the recognition efficiency. The time-frequency transformation of emitter signal is made. The feature vectors are extracted from time-frequency graph using image processing method, which are added class labels. In the dictionary training, the Fisher criterion with small within-class scatter and big between-class scatter is introduced, by which the dictionary not only represents signal more suitably, but also owns better classification performance. The simulated result proves that, compared to analytical dictionary and non-supervision dictionary, the proposed method can obtain a better recognition rate, especially under low SNR. For the atom number N_s=20, Fisher discrimination dictionary can achieve a pretty good balance in recognition rate and calculation amount. Key

Key words: emittersignal, modulationfeature, Fisherdiscrimination, dictionarylearning, time-frequencyanalysis

CLC Number:

TN911.72

WU Xiao-tian, WANG Xing， WANG Zhi-peng， ZHOU Yi-peng, CHEN You. Emitter Signal Modulation Feature Recognition Based on Fisher Discrimination Dictionary Learning[J]. Acta Armamentarii, 2018, 39(3): 553-559.

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第39卷
第3期2018 年3月兵工学报ACTA
ARMAMENTARIIVol.39No.3Mar.2018

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