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摘要
In order to deal with a variety of deception jamming signals based on digital radio frequency memory jammer, this paper presents an algorithm for deception jamming recognition based on sparse representation classification. Firstly, the wavelet packet decomposition and reconstruction are used to divide the signal into different frequency bands, and the feature matrix is constructed by features extracted from the third-order cumulant slice. Then, singular value decomposition is used to reduce the dimension of the feature matrix and extracts the main components. Next, the classification results on each frequency band are obtained by sparse representation classification method, and finally the results are integrated by decision fusion. It has been verified that this method has good anti-noise performance and can effectively identify several common deception jamming signals. When the signal noise ratio is 0 dB, the average recognition rate of deception jamming is more than 90%. Compared with other methods of deception jamming recognition, the superiority of proposed method can be proved. ? 2022 Chinese Institute of Electronics.
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