Emitter Signal Modulation Recognition Based on Stacked Dimension Reduction and Dictionary Learning

doi:10.3969/j.issn.1000-1093.2020.10.012

Abstract

Abstract: A classification and recognition system based on time-frequency features, stacked dimension reduction and dictionary learning is proposed for the problems about low accuracy and timeliness of modulation recognition of emitter signal in a low signal-to-noise ratio environment. The system performs time-frequency transformation and sparse domain noise reduction on the time-domain signals to obtain the two-dimensional time-frequency features and reduce the noise interference. Then it extracts the low-dimensional non-linear features based on unsupervised stacked dimension reduction networks to reduce the feature redundancy. In addition, it improves the timeliness of subsequent processing. Based on multiple discriminant constraints and regular constraints, the discriminative ability and classification timeliness of the dictionary are enhanced to realize the modulation recognition. The simulated results verify the effectiveness and feasibility of the proposed method. The overall average recoghition rate of 7 types of emitter signals, such as single carrier frequency modulation (SCFM) signal, binary frequency shift keying (BPSK) signal, quadrature frequency shift keying (QFSK) signal, linear frequency modulation (LFM) signal, binary phase shift keying (BPSK) signal, quadrature phase shift keying (QPSK) signal, Frank signal, is 95.93% at -8 dB, which has strong robustness and timeliness.

Key words: emittersignalmodulationrecognition, stackeddimensionreduction, dictionarylearning, sparsedomainnoisereduction, regularconstraint, time-frequencyfeature

CLC Number:

TN974

LI Dongjin， YANG Ruijuan， LI Xiaobai， ZHU Shengkun， FEI Taiyong. Emitter Signal Modulation Recognition Based on Stacked Dimension Reduction and Dictionary Learning[J]. Acta Armamentarii, 2020, 41(10): 2023-2032.

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[1]	LI Dongjin， YANG Ruijuan， DONG Ruijie. Emitter Signal Modulation Recognition Based on Joint Projection Dictionary Learning [J]. Acta Armamentarii, 2020, 41(7): 1464-1472.
[2]	GUO Pengcheng, WU Liyang. LPI Radar Signal Recognition with Convolution Feature and Discrimination Dictionary Learning [J]. Acta Armamentarii, 2019, 40(9): 1881-1889.
[3]	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.