Robotics-based location sensing using wireless ethernet
Proceedings of the 8th annual international conference on Mobile computing and networking
A Probabilistic Room Location Service for Wireless Networked Environments
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Location sensing and privacy in a context-aware computing environment
IEEE Wireless Communications
Semi-supervised learning for WLAN positioning
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
A model for WLAN signal attenuation of the human body
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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Location estimation is a crucial component of location-aware applications. Positioning based on received signal strength (RSS) in wireless networks is considered a promising and inexpensive solution. Existing techniques only use RSS from some fixed access points (APs) deployed within the area of interest to estimate user location. Through experiments on the properties of RSS, it is found that RSS from far access points can distinguish different locations more easily. In this paper, we propose to introduce RSS from APs outside of the area to increase location estimation accuracy. We also present an online maximum matching method to select the most possible locations first, thus reducing the computational cost incurred by using more RSS values and improving the speed of location estimation. Our new location estimation method is implemented and compared with related work in a practical wireless network. Experimental results illustrate that the proposed method can give a higher degree of accuracy.