A new optimization approach for indoor location based on Differential Evolution
- https://doi.org/10.2991/ifsa-eusflat-15.2015.229How to use a DOI?
- Indoor Location, WLAN, RSS, Evolutionary Algorithms, Differential Evolution.
The growth of Location Based Services and Location Aware Services in indoor environments has focused the attention of the research community on indoor location systems, especially on those based on WLAN networks and Received Signal Strength (RSS). Despite the advances reached, the development of reliable, accurate and low-cost indoor location systems still remains as an open problem. In this work, we focus on a specific class of location methods where the position of a Mobile Station (MS) is estimated by optimizing a cost function. As far as we know, the optimization models for indoor location proposed so far, only consider the current RSS measurements to estimate the position. In this paper, we propose an optimization approach that uses both current and past measurements to estimate the MS location. To solve the underlying optimization problem we use a Differential Evolution algorithm. The experimentation done over a simulated and a real scenario shows, on the one hand, that using past and current measurements we obtain more accurate and robust position estimations, and on the other hand, that our proposal is competitive versus other high-performing location methods proposed in the literature.
- © 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/).
Cite this article
TY - CONF AU - Antonio D. Masegosa AU - Alfonso Bahillo AU - Enrique Onieva AU - Pedro López-García AU - Asier Perallos PY - 2015/06 DA - 2015/06 TI - A new optimization approach for indoor location based on Differential Evolution BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1604 EP - 1611 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.229 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.229 ID - Masegosa2015/06 ER -