Indoor Position Algorithm Research And Implementation Based On WiFi

In recent years, wireless indoor positioning technology has caused wide attention. At present indoor positioning technology have been applied in many fields, such as the warehouse inventory management, medical treatment, the indoor mobile robot position and so on. Indoor positioning technology demands continue to grow and it promotes the sustainable development of the Uwb positioning technology, infrared positioning technology, ultrasonic positioning technology, Zigbee positioning technology, and Wi Fi positioning technology. Considering the hardware cost and the limit of positioning accuracy, only WiFi of the positioning technology already has a large network coverage, and has the advantages of low cost and low power consumption. Therefore, this thesis selects the WiFi positioning.In this thesis we make a deep research and analysis on the existing Wi Fi indoor localization algorithm. Through the introduction based on signal strength, arrival time, arrival time and arrival angle based on WiFi indoor positioning technology, we analyze and compare the characteristics of each method. Considering the factors such as positioning accuracy and system overhead, this thesis adopts the WiFi positioning algorithm based on signal strength. However, the positioning system based on RSSI is extremely affected by the multipath transmission medium, the signal transmission, and shadow. Even changing the angle of the antenna is likely to affect the ranging accuracy. In order to solve the problems above, this article proposes an indoor optimal positioning algorithm based on WiFi signal strength. It introduces positioning evaluation function, using the optimal algorithm to get a set of path loss exponent to improve the positioning accuracy.On the basis of the algorithm in this thesis we design a set of indoor positioning system based on WiFi. The positioning system is mainly including the positioning server, signal data acquisition terminal, wireless router. Data filtering process and the realization of the localization algorithm, as well as the positioning results present are performed by the server. Experiment results show that the algorithm can obtain higher positioning accuracy without priori information of indoor environment or additional hardware investment.