Research on Radar Active Deception Jamming Identification Method Based on RESNET and Bispectrum Features
Kunteng Wang, Zeyu Dong, Tao Wan, Kaili Jiang, Wanan Xiong, Xueli Fang · 2021 International Conference on Computer Engineering and Application (ICCEA) · 2021
In the complex electromagnetic environment of modern electronic warfare, active deception jamming poses a serious threat to radar. This paper proposes the identification of active deception jamming based on residual neural network (RESNET), and studies the bispectral characteristics of the signal and the method of identifying the active deception jamming of RESNET. This algorithm firstly extracts the bispectral features of the jamming signal, and uses the bispectral diagonal slice as the input of RSNET to realize the recognition of active deception jamming. Simulation results show that the algorithm has high recognition accuracy, not only has good anti-noise performance, but also has excellent robustness under low JSR.