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In recent years, urban rail transit has been developing rapidly, which provides great convenience for passengers. Consequently more and more wireless hot spots are set up along the track. In our paper, the advantages of wireless positioning in urban rail transit are discussed firstly. Then a fingerprinting train positioning algorithm for metro based on deep learning is proposed. The model of fingerprinting positioning and the simulation environment are established to verify the effectiveness of the algorithm. Finally, the results satisfy the accuracy requirements for train positioning in the research on the energy-efficient operation of metro train and it can be used to provide position information for the energy-saving analysis.