关键词: 位置指纹, 最小二乘支持向量, 室内定位

Abstract: Location fingerprints based indoor positioning, which uses wireless AP Received Signal Strength（RSS）, has become a popular research topic during the last a few years. Least Squares Support Vector Machines（LS-SVMs） based fingerprint-positioning is proposed in this paper. First, fingerprint based indoor positioning by LS-SVMs is given. Then, the detailed LS-SVM training process of fingerprinting samples is described. It focuses on how to transfer the positioning problem to a multi-class classification problem, which is handled by One-Against-One（OAO） and One-Against-All（OAA） approach respectively. Simulation results show that the proposed method has higher accuracy（average of 92.00%） and lower computational cost compared with traditional Support Vector Machines（SVMs） and k-Nearest Neighbors（K-NNs）.

Key words: location fingerprints, Least Squares Support Vector Machine（LS-SVM）, indoor positioning