A study of individual identification of radiation source based on feature extraction and deep learning

Abstract Emitter identification technology can distinguish the types of radiation sources and identify the identity of emitter. It has broad application prospects in both military and civilian fields. The article mainly reviews the radiation source feature extraction methods for individual identification in recent years, and discusses the advantages and disadvantages of manually extracted features and the feature extraction based on deep learning. The technical difficulties of radiation source feature extraction methods are summarized with respect to the environment, the number of radiation sources, and the performance of algorithms, etc. Finally, the article points out the possible future development directions of individual radiation source identification.