Robust wireless signal indoor localization

Abstract

Localization is a key enabler of context awareness in computing environments. This paper presents a technique for indoor localization using wireless signal strength from mobile devices. The method described treats locations as fuzzy sets and fuzzifies signal strength‐related features to define membership. Membership values are then fused from multiple sources using a rule engine to deduce objective location values. The principal benefits of this technique are that it requires little or no calibration and that it can be used with widely available commercial devices. Simulation shows that this technique is robust to errors and provides reasonable accuracy. Applications to collaborative workflow and human computer interaction are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 05, 2015
Source ID
10.1002/cpe.3443

Entities

People

  • Gavin Bauer
  • John Hale
  • Liang Kong

Organizations

  • Defense Advanced Research Projects Agency
  • University of Tulsa

Tags

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Sensor Fusion and Tracking Systems.