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Modified Fingerprinting Algorithm for Indoor Location

Xuxing Ding, Li Gao, and Zaijian Wang
College of Physics and Electronic Information, Anhui Normal University, Anhui, China
Abstract—This paper proposes a modified fingerprinting hybrid location algorithm for homogeneous and heterogeneous indoor environment. The new method is designed based on fingerprinting to improve the location accuracy. It works in two phases: one is offline phase, which opts for the location of reference point by different kind of complex regions. Another one is online phase, which proposes dynamic K for finding the nearest reference point to improve location accuracy. Sensor-assisted tracking hybrid positioning function is utilized to further improve the low location accuracy problem of heterogeneous regions. Simulation results show that the new method obtains approximately 37.7% improvement comparing with the classical fingerprinting-based algorithms, the location accuracy reaches to 0.5m in 200m×200m heterogeneous network.
Index Terms—Fingerprinting algorithm, indoor location, dynamic k, sensor-assisted tracking

Cite: Xuxing Ding, Li Gao, and Zaijian Wang, "Modified Fingerprinting Algorithm for Indoor Location," Journal of Communications, vol. 12, no. 3, pp. 145-151, 2017. Doi: 10.12720/jcm.12.3.145-151
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