AN INDOOR SPACE PARTITION METHOD AND ITS FINGERPRINT POSITIONING OPTIMIZATION CONSIDERING 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