Abstract: Aiming at the problem that the sorting clustering positioning algorithm has low matching accuracy, and there are abnormal fingerprint points in the fingerprint points used for position calculation, a Wi-Fi positioning algorithm with matching optimization and distance assistance is proposed. According to the user's front and back position, distance and step length, a matching deviation detection model is designed to determine the user's abnormal position and matching deviation; the adjacent elements in the sorted received signal strength vector are compared with the set threshold to determine the change position of the sorting feature vector of the point to be located, achieve the purpose of correction by exchange, and obtain the corrected and merged class matching result; according to the distance between the user's position determined in the time period m before the positioning and the fingerprint point in the matching class, the abnormal fingerprint points used for position calculation are eliminated, so as to achieve more accurate indoor positioning. The simulation results show that the class matching accuracy and the average positioning accuracy of the proposed algorithm are improved respectively by 17% and 22%.