| Automatic Intrapulse Modulated LPI Radar Waveform Identification |
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Minjun Kim, Seung-Hyun Kong |
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The CCS Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology |
| 펄스 내 변조 저피탐 레이더 신호 자동 식별 |
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김민준, 공승현 |
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한국과학기술원 조천식녹색교통대학원 |
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| Abstract |
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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. |
| Key Words:
LPI Radar, Intrapulse Modulation, Convolutional Neural Network, Parameter Extraction |
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