Aiming at improving the deficiency of positioning accuracy of moving targets such as underground personnel, vehicles and equipment, this paper studies the location algorithm and fingerprint location model of mine moving target and a fusion location method based on SVR model optimized by improved particle swarm optimization and Chan distance fingerprint is proposed. Firstly, an ultra wideband (UWB) core node model based on STM32 ARM main controller and DWM1000 is designed, and the transmission distance data are analyzed through bilateral bidirectional ranging and time of flight ( TOF). On this basis, the moving path of the target is predicted by successively collecting distance fingerprints at specific points and the moving target route fitting within the improved PSOSVR model. Then it is combined with the Chan algorithm fingerprint, and expand the optimized distance fingerprint fusion location method. The experimental results show that the optimized distance fingerprint fusion location method can correctly predict the moving path, with the maximum error of no more than 20 cm and the average error of no more than 1 cm. The study is of great significance to mine intelligent construction and safety production.