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Publication Type : Journal Article
Publisher : International Symposium on Web and Wireless Geographical Information Systems
Source : International Symposium on Web and Wireless Geographical Information Systems, Springer Verlag, Volume 11474 LNCS, p.174-187 (2019)
ISBN : 9783030172459
Keywords : calibration, Cost effectiveness, Distance estimation, Dual Band, Environmental factors, Geographic information systems, Heuristic methods, IEEE Standards, Indoor localization systems, Indoor localization techniques, Indoor positioning systems, Information systems, Information use, Iterative methods, Location based services, Mathematical models, Optimization strategy, Smartphones, Surveying, Telecommunication services, Trilateration, Wifi signal strengths, Wireless local area networks (WLAN)
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2019
Abstract : WiFi based indoor and semi-indoor localization techniques are essential components of indoor location-based services. Calibration-free techniques for WiFi signal strength based indoor localization can help make indoor localization systems scalable, cost-effective and easy to deploy. However, distance estimation errors and environmental factors affect the accuracy of non-calibration solutions like trilateration significantly, and addressing the accuracy issue is critical. To help improve accuracy, localization over dual-band WiFi (IEEE 802.11n) which uses both 2.4Â GHz and 5Â GHz bands is a potential alternative. This paper proposes a novel adaptive, weighted trilateration technique that uses the behavior of these two bands under different conditions. An iterative heuristic approach based on the characterization of the behavior of the bands is employed to determine the most likely position of a smart phone. Additionally optimization strategies are applied to improve the time complexity of this approach. Experiments conducted in different indoor environments show that our approach performs better than other non-calibration signal strength based approaches in terms of accuracy, and also reduces the worst case error. © 2019, Springer Nature Switzerland AG.
Cite this Research Publication : S. Mathivannan, Srinath, S., Shashank, R., Aravindh, R., and Dr. Vidhya Balasubramanian, “A Dynamic Weighted Trilateration Algorithm for Indoor Localization Using Dual-Band WiFi”, International Symposium on Web and Wireless Geographical Information Systems, vol. 11474 LNCS, pp. 174-187, 2019.