WLAN Indoor Localization Algorithm Based on Manifold Interpolation Database Construction
ZHOU Mu①② TANG Yunxia① TIAN Zengshan① WEI Yacong①
①(Chongqing Key Laboratory of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) ②(Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin 300387, China)
To deal with the high cost involved in the location fingerprint database construction due to the dense Reference Points (RPs) distribution and point-by-point Received Signal Strength (RSS) collection in the conventional Wireless Local Area Network (WLAN) indoor localization systems, a new database construction approach based on the integrated semi-supervised manifold learning and cubic spline interpolation is proposed. The proposed approach utilizes a small amount of labeled data and a massive amount of unlabeled data to find the optimal solution to localization target function, and meanwhile relies on the mapping relations between the high-dimensional signal strength space and low-dimensional physical location space to calibrate the unlabeled data with location coordinates. The extensive experiments demonstrate that the proposed approach is able to guarantee the high localization accuracy, as well as significantly reduce the cost involved in location fingerprint database construction.
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