An indoor positioning and navigation technique based on Wi-Fi fingerprint and environment information

With the development of urbanization in recent years, the conditions for building the smart city gradually mature, the increase in large airports, shopping centers and office buildings makes indoor positioning and navigation services more important. The satellite signal in indoor environment is too weak to locate, while notebook computers, mobile phones and other intelligent terminals greatly increase, and Wi-Fi signals become more dense and extensive, which provide the material foundation for the development of indoor positioning technology. In order to solve the indoor positioning problem, we propose an indoor positioning and navigation technique based on Wi-Fi fingerprint and environment information. The user’s intelligent terminal can detect the signal strength of each wireless access point and obtain the received signal strength indication (RSSI), then the specific location of the device can be calculated according to the indoor radio pass loss model and Wi-Fi signal strength fingerprint database composed by each node. The combination of k nearest neighbor (k-NN) algorithm and particle filter (PF) algorithm helps to improve the positioning accuracy and robust stability in the paper, and the combination of the Dijkstra algorithm and Wi-Fi fingerprint database based on reference nodes provides the optimal navigation route by calculating the shortest path from the start position to destination. Simulation experiment was carried out on the 4th floor of new main building of Beihang University, from which we obtain the location map and the navigation route map from the starting point to destination. The experiment result shows the efficiency and reliability of the algorithm.