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Mobile Information Systems
Volume 2016, Article ID 8765874, 11 pages
http://dx.doi.org/10.1155/2016/8765874
Research Article

IWKNN: An Effective Bluetooth Positioning Method Based on Isomap and WKNN

Department of Mathematics, Northeastern University, Shenyang, Liaoning Province, China

Received 2 July 2016; Revised 21 September 2016; Accepted 29 September 2016

Academic Editor: Ruay-Shiung Chang

Copyright © 2016 Qi Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Recently, Bluetooth-based indoor positioning has become a hot research topic. However, the instability of Bluetooth RSSI (Received Signal Strength Indicator) promotes a huge challenge in localization accuracy. To improve the localization accuracy, this paper measures the distance of RSSI vectors on their low-dimensional manifold and proposes a novel positioning method IWKNN (Isomap-based Weighted -Nearest Neighbor). The proposed method firstly uses Isomap to generate low-dimensional embedding for RSSI vectors. Then, the distance of two given RSSI vectors is measured by Euclidean distance of their low-dimensional embeddings. Finally, the position is calculated by WKNN. Experiment indicates that the proposed approach is more robust and accurate.