Volume XLI-B4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 347-350, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-347-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 347-350, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-347-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  13 Jun 2016

13 Jun 2016

AN INDOOR SPACE PARTITION METHOD AND ITS FINGERPRINT POSITIONING OPTIMIZATION CONSIDERING PEDESTRIAN ACCESSIBILITY

Yue Xu1, Yong Shi1,2, Xingyu Zheng1, and Yi Long1 Yue Xu et al.
  • 1School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
  • 2School of Information Engineering, Nanjing Normal University Taizhou College, Taizhou 225300, China

Keywords: In-door Navigation, Space Partition, Fingerprint, Position Algorithm, Pedestrian Accessibility

Abstract. Fingerprint positioning method is generally the first choice in indoor navigation system due to its high accuracy and low cost. The accuracy depends on partition density to the indoor space. The accuracy will be higher with higher grid resolution. But the high grid resolution leads to significantly increasing work of the fingerprint data collection, processing and maintenance. This also might decrease the performance, portability and robustness of the navigation system. Meanwhile, traditional fingerprint positioning method use equational grid to partition the indoor space. While used for pedestrian navigation, sometimes a person can be located at the area where he or she cannot access. This paper studied these two issues, proposed a new indoor space partition method considering pedestrian accessibility, which can increase the accuracy of pedestrian position, and decrease the volume of the fingerprint data. Based on this proposed partition method, an optimized algorithm for fingerprint position was also designed. A across linker structure was used for fingerprint point index and matching. Experiment based on the proposed method and algorithm showed that the workload of fingerprint collection and maintenance were effectively decreased, and poisoning efficiency and accuracy was effectively increased