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| Active Suppression Jamming Recognition Based on RBF Neural Network |
| DAI Shaohuai， YANG Gewen， YU Wen， WU Xiangshang |
| Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China |
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Abstract In order to solve the problem of low recognition accuracy due to improper selection of signal characteristics in the process of jamming recognition by radar in modern electronic warfare, a jamming recognition method based on RBF neural network combined time-frequency domain analysis is proposed. This method proposes to combine the time-frequency domain characteristics of the jamming signal and take the advantage of the fast convergence speed and strong nonlinear fitting ability of the RBF neural network to improve the recognition probability of radar against active suppression jamming. The simulation results show that the RBF neural network based on time-frequency domain analysis can guarantee a high jamming recognition probability.
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Received: 10 January 2022
Published: 25 March 2022
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2022, Vol. 5 
