A New GPS/RFID Integration Algorithm Based on Iterated Reduced Sigma Point Kalman Filter for Vehicle Navigation

J. Peng, F. Wu, M. Zhu, K. Zhang, F. Wang

Abstract:	To improve the accuracy, reliability and availability of GPS navigation service in urban area, a new GPS/RFID integration method for vehicle navigation is proposed in this paper. In the proposed method, a RFID system is used to aid GPS to achieve a high accuracy positioning via the Received Signal Strength (RSS) measurements and sparse location information of RFID tags. An iterated Reduced Sigma Point Kalman Filter is proposed as a predominant filter for the GPS/RFID integration as well. The results of field experiment show that both accuracy and availability of positioning can be improved by this low-cost GPS/RFID integration method significantly.
Published in:	Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009) September 22 - 25, 2009 Savannah International Convention Center Savannah, GA
Pages:	803 - 810
Cite this article:	Peng, J., Wu, F., Zhu, M., Zhang, K., Wang, F., "A New GPS/RFID Integration Algorithm Based on Iterated Reduced Sigma Point Kalman Filter for Vehicle Navigation," Proceedings of the 22nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2009), Savannah, GA, September 2009, pp. 803-810.
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