基于模糊函数多域特征自适应融合的雷达辐射源信号识别OA

To address the problems of insufficient feature utilization and poor noise resistance in current radar emit-ter signal recognition methods for complex systems,a recognition method based on multi-domain feature adaptive fusion with ambiguity function is proposed.First,an integral-accelerated ST-NLM algorithm is employed to denoise the signal ambiguity function,and the filtering coefficient is adaptively adjusted through the structure tensor.Then,multi-domain projection features are extracted from the time-delay domain,Doppler frequency domain,and joint time delay-Doppler domain.Finally,a ResNet+adaptive attention feature fusion(AAFF)model is constructed,utilizing multi-scale dilated convolution,depthwise separable convolution,and efficient channel attention(ECA)mechanism to achieve adaptive fea-ture fusion.Experimental results show that the method can maintain 100%accuracy when the signal-to-noise ratio(SNR)is above 0 dB,and even at-4 dB SNR,the recognition rate can still reach 98.12%.It validates that the proposed method has certain effectiveness and feasibility under low SNR conditions.