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Fuze play an important role in electronic warfare nowadays. With the continuous development of jamming means, the development of intelligent fuze anti-jamming is imminent. Now the recognition of fuze jamming signal is the prerequisite to realize intelligent fuze anti-jamming. In order to enhance the anti-jamming ability of the fuze, first we should accurately recognize the fuze jamming signal. Traditional fuze jamming recognition schemes usually accomplish the recognition by manually extracting the signal features in the time or frequency domain. However, the accuracy achieved by traditional recognition methods is limited. Moreover, extracting the features of the fuze jamming signals by traditional methods becomes more and more complicated and is hard to be practically implemented. To address the limitations imposed by traditional methods, we propose a fuze jamming signal detector based on time-frequency analysis and convolutional neural network (TFA-CNN). |
IEEE/ICACT20230135 Slide.03
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