对调制识别网络隐身的雷达发射信号生成方法

Radar transmitting signal generation method for modulation recognitionnetwork stealth

雷达对抗场景中,电子侦察系统通过引入基于深度学习方法的智能脉冲调制识别网络,极大提升了对雷达信号的识别准确率。为了提高雷达信号的调制隐身抗识别能力,提出一种可以令深度识别网络错误预测的雷达发射信号生成方法。该方法首先通过短时傅里叶变换得到信号的时频谱;然后迭代生成携带调制隐身信息的时频谱;最后利用改进逆短时傅里叶变换得到时域调制隐身发射信号。该方法生成的雷达信号对以时频图为输入的调制识别网络隐身,并可实现回波信号的脉冲压缩处理。仿真结果验证了所生成信号的抗识别有效性、噪声鲁棒性和脉压可行性。

The electronic reconnaissance system in radar countermeasure scenarios greatly improves the recognition accuracy of radar signals by introducing an intelligent pulse modulation recognition network based on deep learning methods.In order to improve the modulation stealth and anti-recognition ability of radar signals,a radar transmission signal generation method that can make the deep recognition network make incorrect predictions is proposed.Firstly,the time-frequency spectrum of the signal is obtained through short-time Fourier transform(STFT).Then,a time-frequency spectrum carrying modulated stealth information is generated iteratively.Finally,the improved inverse STFT is used to obtain the time-domain modulated stealth transmission signal.The radar signal generated by the proposed method is invisible to the modulation recognition network input from the time-frequency map,and can achieve pulse compression processing of the echo signal.The simulation results verified the effectiveness of the generated signal in resisting recognition,noise robustness,and pulse compression feasibility.