Aiming at the problems of poor anti-noise performance and low recognition accuracy in radar emitter signal recognition method in complex electromagnetic environment. An integrated deep learning recognition method based on multi-domain projection features of ambiguity function was proposed. First, an ambiguity function is processed by using a Gaussian operator, Secondly, from the multi-domain perspective, select the appropriate angle to carry out two-dimensional projection to build a characteristic data set. Then, a two-stage recognition and classification method based on multi domain feature fusion is constructed. Multiple dense connected networks DenseNet121 are used as primary classifiers to train and learn the three kinds of feature data sets respectively, and the primary classification results are obtained; Finally, the results of the primary classification result is integrated through the Stacking policy to obtain the final classification result. The experimental results show that the overall average recognition rate of the six types of typical radar signals is above 97.24%, when the signal-to-noise ratio is 0 dB, even in the -4db environment, the recognition rate is also stable in 87.16%, Verify the effectiveness and feasibility of the method, have a certain engineering value.