Small sample radar one-dimensional image target identification method based on deep transfer learning

The invention belongs to the technical field of radar target recognition, and particularly relates to a small sample radar one-dimensional image target recognition method based on deep transfer learning. Aiming at a radar one-dimensional image under a small sample condition, firstly, a feature extraction network is pre-trained on a source data set, a mixed attention mechanism and a smooth label are used to improve the recognition precision and generalization performance of a model, then the feature extraction network is fixed, and the recognition precision and generalization performance of the model are improved. The distribution of small sample data is calibrated on a target data set by using a distribution calibration strategy, and data is generated from new distribution to jointly train a classifier with real small sample data, so that the model recognition precision under the small sample condition is improved. According to the method, the problem that the model is difficult to train under the condition o