The identification of power IoT devices on differential constellation trajectory map

As a long-distance wireless transmission technology based on spread spectrum, LoRa is a hot research object in the field of power Internet of Things. To solve the problem of terminal authentication, this paper proposes a LoRa device identification method based on a differential constellation trajectory map, which skillfully transforms the radiofrequency fingerprint feature matching problem into the image processing problem. This method first obtains the constellation locus of the received signal. It performs differential processing and then USES the clustering algorithm to get the constellation locus's clustering center. It then calculates the Euclidean distance between the clustering centers of two devices to obtain the similarity between them and USES this as a basis for equipment identification. The experimental results show that the LoRa device recognition method based on differential constellation trajectory map can effectively identify five LoRa transmission modules and have a high recognition accuracy even in low SNR.