基于卡方距离及灵敏度法的无线局域网室内定位方法

WLAN localization service has become an field of research for smarter city nowadays. Among the localization algorithm, the classic Euclidean distance method solely keeps count of the absolute distance between the RSSI vector and overlooks the relative distance between the RSSI vector. And it can only give the same weight to every AP. This paper indicates a new algorithm based on Chi-Square Distance and Sensitivity Method for WLAN indoor localization. The proposed algorithm uses fingerprinting technique to make training dataset and testing dataset, then uses Chi-Square Distance and Sensitivity Method to correct the training dataset which will be used in the online localization phase and get the weight of every AP in the algorithm in order to improve positioning accuracy. The results show that the proposed algorithm has better accuracy compared with the classical fingerprinting techniques.