Wireless Indoor Positioning Algorithm Based on PCA

DOI

10.2991/aiie-15.2015.3How to use a DOI?

Keywords

WLAN; PCA; KNN; Localization

Abstract

The use ofWLAN (Wireless Local Area Networks)for indoor localization is an important content in the field of mobile Internet, usually based on the Received Signal Strength(RSS) and the fingerprinting algorithms. Due to the characteristics of the RSS, environmental factors have great influence on the RSS value. So this paper proposes to extract RSS feature samples using the PCA (Principal Component Analysis)and use the KNN(k-Nearest Neighbouralgorithm) to locate. The simulation show that the algorithm has the stronger ability of anti-jamming and better positioning accuracy than theKNN(k-Nearest Neighbouralgorithm) algorithm.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - H.L. Li
AU  - W. Quan
AU  - G. Ji
AU  - Z.H. Qian
PY  - 2015/07
DA  - 2015/07
TI  - Wireless Indoor Positioning Algorithm Based on PCA
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 8
EP  - 9
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.3
DO  - 10.2991/aiie-15.2015.3
ID  - Li2015/07
ER  -