펄스 내 변조 저피탐 레이더 신호 자동 식별 Automatic Intrapulse Modulated LPI Radar Waveform Identification

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In electronic warfare(EW), low probability of intercept(LPI) radar signal is a survival technique. Accordingly, identification techniques of the LPI radar waveform have became significant recently. In this paper, classification and extracting parameters techniques for 7 intrapulse modulated radar signals are introduced. We propose a technique of classifying intrapulse modulated radar signals using Convolutional Neural Network(CNN). The time-frequency image(TFI) obtained from Choi-William Distribution(CWD) is used as the input of CNN without extracting the extra feature of each intrapulse modulated radar signals. In addition a method to extract the intrapulse radar modulation parameters using binary image processing is introduced. We demonstrate the performance of the proposed intrapulse radar waveform identification system. Simulation results show that the classification system achieves a overall correct classification success rate of 90 % or better at SNR = -6 dB and the parameter extraction system has an overall error of less than 10 % at SNR of less than -4 dB.
Publisher
한국군사과학기술학회
Issue Date
2018-04
Language
Korean
Citation

한국군사과학기술학회지, v.21, no.2, pp.133 - 140

ISSN
1598-9127
DOI
10.9766/KIMST.2018.21.2.133
URI
http://hdl.handle.net/10203/247003
Appears in Collection
GT-Journal Papers(저널논문)
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