Dead-reckoning Aided RSSI Based Positioning System for Dynamic Indoor Environments

W-W. Kao, S-H. Lin

Abstract:	Indoor positioning based on received signal strength index, or RSSI, is quite popular idea and has been realized by using several wireless networks such as Wi-Fi, Bluetooth, Zigbee, etc. In the implementations, a signal propagation model is used to characterize the relationship between the measured RSSI and the signal transmitting distance in order to determine the unknown user location with respect to transmitters in known fixed locations. RSSI measurements have large variations because they are subjected to the deleterious effects of fading or shadowing in dynamic indoor environments and it is difficult to model these effects using fixed propagation model parameters. Dead-reckoning based systems which detect the user relative motions by various sensors are also popular in indoor positioning applications. This research integrates the relative displacement information from dead-reckoning systems with a Zigbee RSSI-based positioning system. Unlike conventional systems, the RSSI model parameters are not consider known or fixed but are estimated together with the unknown user locations during the motion using both the Extended Kalman filter (EKF) and the Particle filter (PF). With the capability to dynamically estimate the signal propagation model parameters in changing environments, the positioning accuracy is improved and the integrated system is more suitable to be used in dynamic indoor environments with signal propagation variations. Both simulation and experiments results are presented to show the performance of the integrated positioning system in indoor environments.
Published in:	Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010) September 21 - 24, 2010 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	3359 - 3365
Cite this article:	Kao, W-W., Lin, S-H., "Dead-reckoning Aided RSSI Based Positioning System for Dynamic Indoor Environments," Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010), Portland, OR, September 2010, pp. 3359-3365.
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