基于多域特征的多雷达信号自动识别方法

Automatic recognition method of multi-radar signals based on multi-domain features

为解决复杂电磁环境中多台雷达在相似的频段上同时发射各自的信号,导致侦察接收信号在时域和频域上重叠的问题,提出一种低信噪比(SNR)下自动调制识别(MR)方法。通过接收脉冲间列快速傅里叶变换(FFT)将接收信号的能量集中在各自的多普勒频率上,以达到分离多个截获信号的目的;将每个信号的Wigner-Ville分布(WVD)和模糊函数(AF)作为一幅图像的2层同时发送到训练后的残差神经网络(ResNet),以解决某些类型的信号仅采用单一时频分布时识别精度低的问题。理论分析和仿真结果表明:所提方法不仅能有效分离时域和频域重叠的多个雷达信号,而且能在SNR为-10 dB的条件下准确识别其调制模式。

In complex electromagnetic environments,simultaneous signal transmission of multiple radars in similar frequency bands can cause overlapping of reconnaissance’s received signals in the time and frequency domains.To address this problem,an automatic modulation recognition(MR)method with a low signal-to-noise ratio(SNR)is proposed.The energy of the received signal is concentrated on the respective Doppler frequency through the row FFT transformation between the received pulses to achieve the separation of multiple intercepted signals.The Wigner-Ville distribution(WVD)and ambiguity function(AF)of each signal are simultaneously sent to the trained residual neural network(ResNet)as two layers of an image to solve the problem of low recognition accuracy when some types of signals only use a single time-frequency distribution.Theoretical analysis and simulation results show that the proposed method can not only effectively separate multiple radar signals overlapping in the time and frequency domains,but also accurately identify their modulation modes with the SNR of−10 dB.