Research on WiFi Fingerprint Location Algorithm Based on Fusion Clustering

• 1、School of Mechanical Electronic and Information Engineering, China University of Mining and Technology-Beijing，Beijing 100083

Abstract：Wireless location technology is expensive and difficult to deploy, and similar fingerprints in RSS indoor fingerprint location are prone to mismatching. Aiming at the problem, the WiFi fingerprint locating algorithm based on fusion clustering was proposed. Fuzzy C-means (FCM) clustering is adopted instead of the traditional hard clustering algorithm. Because FCM algorithm can reasonably estimate the characteristics of RSS in clustering center and avoid errors generated by hard clustering algorithm. It also can increase the difference between the reference points and reduce the complexity of feature matching. But FCM algorithm tends to converge to local extreme values under the influence of initial values. Aiming at the problem, this paper use density peaks clustering (DPC) algorithm to effectively correct the shortcomings of FCM algorithm. Because DPC algorithm can accurately characterize the initial center of clustering. Therefore this way can improve the positioning accuracy. The experimental results show that the localization algorithm based on FCM and DPC is more accurate than that based on traditional clustering.

Keywords： Indoor location Fuzzy C-means clustering density peaks clustering algorithm