Adaptive Affine Propagation Clustering Algorithm for WiFi Indoor Positioning

There are a large number of indoor WiFi signals which can be used for indoor positioning. Although many WiFi indoor positioning technology is proposed, it's positioning accuracy still does not meet the actual application requirements. For this problem, an Adaptive Affinity Propagation Clustering (AAPC) algorithm is proposed to improve the clustering quality of WiFi fingerprint, thus improving the positioning accuracy. The AAPC algorithm generates different clustering results by dynamically adjusting parameters, then cluster validity indices are used to select the best ones. A large number of real environmental data are collected and tested. The experimental results show that the clustering results generated by AAPC algorithm have higher positioning accuracy.