Error characteristics and calibration-free techniques for wireless LAN-based location estimation
Proceedings of the second international workshop on Mobility management & wireless access protocols
Adaptive Temporal Radio Maps for Indoor Location Estimation
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
Sensor-assisted wi-fi indoor location system for adapting to environmental dynamics
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Calibration-free WLAN location system based on dynamic mapping of signal strength
Proceedings of the 4th ACM international workshop on Mobility management and wireless access
An RSS Localization Method Based on Parametric Channel Models
SENSORCOMM '07 Proceedings of the 2007 International Conference on Sensor Technologies and Applications
A Survey on Wireless Position Estimation
Wireless Personal Communications: An International Journal
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Received signal strength-based localization systems usually rely on a calibration process that aims at characterizing the propagation channel. However, due to the changing environmental dynamics, the behavior of the channel may change after some time, thus, recalibration processes are necessary to maintain the positioning accuracy. This paper proposes a dynamic calibration method to initially calibrate and subsequently update the parameters of the propagation channel model using a Least Mean Squares approach. The method assumes that each anchor node in the localization infrastructure is characterized by its own propagation channel model. In practice, a set of sniffers is used to collect RSS samples, which will be used to automatically calibrate each channel model by iteratively minimizing the positioning error. The proposed method is validated through numerical simulation, showing that the positioning error of the mobile nodes is effectively reduced. Furthermore, the method has a very low computational cost; therefore it can be used in real-time operation for wireless resource-constrained nodes.