Study On Indoor Fingerprint Positioning Technology Based On WLAN And Bluetooth

With the increasing coverage of WLAN networks and wireless sensor networks, and the increasing demand of location-based services, indoor positioning system based on all kinds of wireless networks has become a hot research topic. It shows great potential applications in the field of emergency relief, logistics storage, information push and other. According to the complex indoor environment, single wireless network positioning technology is often difficult to ensure the effective coverage of the positioning signal and high precision positioning performance. Therefore, the thesis studies indoor positioning technology based on WLAN location fingerprint location technology as the core and Bluetooth network. The main research work includes the following three aspects.First of all, according to the problem of setting up the workload of fingerprint database in the offline phase of WLAN fingerprint location technology, presents an ordinary Kriging spatial interpolation construction algorithm based on signal attenuation factors. The method uses spherical model to fit spatial variogram function and obtains other position signal strength valuation by ordinary Kriging spatial interpolation to generate corresponding location fingerprinting. A large capacity and high resolution position fingerprint database is generated to reduce workload of position fingerprint parameter acquisition. The simulation results show that the algorithm not only ensures accuracy, but also reduces the workload of about 40%.Then, in order to improve positioning accuracy of WLAN location fingerprint positioning technology, this thesis presents a data division KNN_ filter matching location algorithm. The method uses improved K-means data partition, effective selection of AP, and KNN matching algorithm to complete the positioning accuracy estimation. The simulation results show that the algorithm improves the positioning accuracy and reduces the data redundancy, as well as reduces the matching complexity.Finally, in order to make better use of network resources and improve the positioning accuracy of the system, the thesis proposes a fusion location algorithm based on location fingerprint and adaptive APIT to complete fusion positioning. The improved APIT adaptive Bluetooth algorithm is used to estimate the position of the measuring points. The estimation results and WLAN location fingerprinting localization algorithms positioning results complete weighted average to determine the optimal position of the measured point estimation. Simulation results show that the positioning effect based on the fusion network positioning algorithm is superior to the single network positioning effect, and the positioning accuracy is improved.