Improved ZigBee Fingerprint Method for Indoor Positioning

X. Liu, H. Guo, M. Yu, Y. Li

Abstract:	After researching ZigBee network fingerprint method for data collection and building database, a new improved method for the fingerprint database establishment has been proposed in this paper. The novel method processes data by filtering algorithm for improving the database accuracy. The following two steps have been completed. The first step: all collected data of fingerprint database source from every sampling point have been filtered, and then is used for establishing high accurate fingerprint database in the positioning area. The second step: the nearest algorithm, weighted nearest algorithm and Bayesian algorithm have respectively been used to calculate pedestrian's location. All results show that the standard deviation with the improved fingerprint database is less than or equal to 0.9 meters in a short distance range for the nearest algorithm. That's much better than that reported by us or other researchers before. Recent progress indicated that the distance achieved by our hardware has been extended to nearing 40 meters without decreasing the positioning accuracy, so the system can be applied in a bigger space inside the buildings or the underground mines.
Published in:	Proceedings of the ION 2013 Pacific PNT Meeting April 23 - 25, 2013 Marriott Waikiki Beach Resort & Spa Honolulu, Hawaii
Pages:	616 - 623
Cite this article:	Liu, X., Guo, H., Yu, M., Li, Y., "Improved ZigBee Fingerprint Method for Indoor Positioning," Proceedings of the ION 2013 Pacific PNT Meeting, Honolulu, Hawaii, April 2013, pp. 616-623.
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