WKNN indoor location clustering algorithm with triangle correction

Aiming at the problem of low precision in the positioning stage of fingerprint location positioning technology based on WiFi, through the comparative study of the nearest neighbor classification algorithm (NN), K nearest neighbor classification algorithm (KNN) and Bias algorithm, and then we present a kind of weighted KNN algorithm of based on triangle correction. On the one hand, the algorithm uses the difference between the AP signal intensity value of the node and the fingerprint node to be taken as the weighting factor, and the positioning accuracy of KNN is improved by the contribution ratio of different fingerprint nodes; On the other hand, we further improve the positioning accuracy by selecting three nearest neighbor points which the unknown node must be in the triangle composed of these three points. Finally, the simulation results showed the effectiveness of the algorithm.