A KNN Indoor Positioning Algorithm That Is Weighted by the Membership of Fuzzy Set

An indoor positioning algorithm that based on the theory of fuzzy set is presented to overcome the deficiencies of classic KNN positioning algorithm in Wi-Fi wireless network environment. The algorithm takes individual reference point as a fuzzy set and establishes its membership function. For the location that need to positioning, taking the membership of reference point fuzzy set that as weight, and calculating the weighted average coordinate of reference points as estimated coordinate for the targeted position. The algorithm was implemented on Android platform and its performance was analyzed. The experiment shows that the algorithm is simple and has good position accuracy, which is significant for the practical use of indoor positioning system.