RESEARCH ON KNOWLEDGE-BASED OPTIMIZATION METHOD OF INDOOR LOCATION BASED ON LOW ENERGY BLUETOOTH
- 1Key Laboratory for Geographical Process Analysis & Simulation, Hubei Province, Central China Normal University, Wuhan, China
- 2College of Urban and Environmental Science, Central China Normal University, Wuhan, China
- 3School of Land Science and Technology, China University of Geosciences, Xueyuan Road 29, Haidian District, Beijing 100083, China
Keywords: Indoor Location; Low Energy Bluetooth; Visibility Analysis; Robust Regression Estimation; Random Sampling Consensus; Indoor 3D Map
Abstract. With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.