Space division and dimensional reduction methods for indoor positioning system

Yun Mo, Zhongzhao Zhang, Weixiao Meng, Gul A Agha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the popularity of smart phones and the development of mobile computing, indoor positioning services have triggered large scale of technology innovation and commercial cooperation. In the field of Wi-Fi based fingerprinting positioning system, for one thing, we deploy space division method based on Random Forest for dividing the fingerprinting radio map into sub regions freely and classifying candidate points accurately. For another thing, we propose a dimension reduction method, which integrates Maximum Likelihood Estimation for estimating intrinsic dimensionality and Kernel Principal Component Analysis for feature extraction, to tremendously reduce the size of a radio map, thereby saving terminal storage and alleviating error margin. Compared with linear feature extraction methods and manifold learning techniques, the proposed method shows a better performance in low dimension. The experimental results demonstrate that the proposed indoor positioning system, which is based on the given space division and dimension reduction techniques, could achieve 98% space division accuracy, 85% confidence probability with 2m positioning error and reduce 74% size of the radio map in addition to its noise suppression ability.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Communications, ICC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3263-3268
Number of pages6
ISBN (Electronic)9781467364324
DOIs
StatePublished - Sep 9 2015
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: Jun 8 2015Jun 12 2015

Publication series

NameIEEE International Conference on Communications
Volume2015-September
ISSN (Print)1550-3607

Other

OtherIEEE International Conference on Communications, ICC 2015
Country/TerritoryUnited Kingdom
CityLondon
Period6/8/156/12/15

Keywords

  • KPCA
  • MLE
  • RF
  • indoor positioning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Space division and dimensional reduction methods for indoor positioning system'. Together they form a unique fingerprint.

Cite this