For the specific emitter identification method, fingerprint feature extraction needs complex formula calculus reasoning, the feature difference is small, the extraction is difficult, and the accuracy of specific emitter identification after extraction is low. In order to better extract fingerprint features, a specific emitter identification algorithm based on dense connection structure and attention mechanism is proposed, which is called specific emitter identification network ( SEIN). First, the envelope extraction algorithm is used to extract the envelope of the radiation source signal with less noise, and an envelope map with rich fingerprint features is obtained, then the SEIN fingerprint feature extraction and individual recognition are performed. The experimental results show that SEIN can achieve a classification and recognition effect of 95. 12%, has the characteristics of high accuracy and automatic fingerprint feature extraction, and finally achieves better specific emitter identification in complex environments.