关键词: 室内定位, 接收信号强度, 接入点（AP）选择, 连续互信息

Abstract: Aiming at solving the problem that access points of wireless indoor location have correlation and regional, a novel improved algorithm called OCUMI （Online Continuous source of Union Mutual Information） is proposed. Considering the correlation between the access points, a self-adaptive access point selection algorithm based on mutual information and entropy is proposed in online phase. The correlation between access points is measured through continuous source joint mutual information； at the same time, combining the information entropy to search the access points which contain most valid information about the location. Finally, Kullback-Leibler divergence is used to match position, and estimate the node position. The performance evaluation is conducted at the premises of a research laboratory and a conference room under real-life conditions. Experimental results show that, compared with WKNN and MLE, the proposed OCUMI algorithm has better localization accuracy.

Key words: indoor localization, received signal strength, Access Point（AP） selection, continuous mutual information