Compared with the WKNN algorithm, the traditional EWKNN algorithm can effectively improve the positioning accuracy, but there is still a problem that the localization result has a long jump span in space. Aiming at the shortcomings of the traditional EWKNN algorithm, this paper proposes an indoor localization algorithm based on multiple constraint matching based on the EWKNN algorithm. The algorithm takes the correlation between the front and rear position of the pedestrian into account, and uses the predicted position of the previous step to constrain the WiFi matching of the current step many times, and remove the distant reference points from the matching. Experiments show that compared with the traditional EWKNN algorithm, this algorithm has a higher positioning accuracy.