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With the advantages of LoRa in anti-interference, low power consumption and low cost, a vehicle positioning system based on LoRa for underground parking lots is designed. The NLOS delay model is analyzed in the special communication environment of underground parking lots. In this paper we combine the sorting algorithm with the typical mean filtering algorithm to overcome the downside of the typical mean filtering algorithm that the impulse noise can only be shared equally in the filter window and cannot be completely eliminated. Besides, we use the method of parameter fitting to suppress the regular NLOS delay in underground parking environment and processing the error of the label node module. We also optimize the Trilateration Method to improve the accuracy of positioning and avoid the situation of the occurrence of no solution. The system is applied in actual environment and the feasibility of the system is verified.