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.
戴少怀, 杨革文, 郁文, 吴向上. 基于RBF神经网络的雷达有源压制干扰识别[J]. 空天防御, 2022, 5(1): 102-107.
DAI Shaohuai, YANG Gewen, YU Wen, WU Xiangshang. Active Suppression Jamming Recognition Based on RBF Neural Network. Air & Space Defense, 2022, 5(1): 102-107.
