一种利用 RFID 和块聚类的快速室内指纹定位方法

The indoor positioning technology based on fingerprint attracts the attentions from many researchers. RFID (Radio Frequency Identification) technology is more attractive, due to its high accuracy and adaptability to different environment. However, because of the heavy consumption of the computing power, it limits the applications in practice. A new hybrid Kmeans and Weighted K-Nearest Neighbor method is proposed and applied in real-world indoor positioning. The new method divided the mapping area into several classes based on a clustering method. A matching into class is done first and then location is determined. The result shows that the proposed method reduces the accumulated errors and thus reduces the computational power whist maintains reasonable accuracy.