A Smartphone Indoor Localization Method Based On WiFi And Inertial Sensors

With the rapid development of mobile internet, people are now used to the location based services such as location sign in, local search and navigation. The localization technology serves as the cornerstone of location based services, the accuracy it provides decides the quality of these services. Although outdoor localization technologies like GPS have been widely adopted, accurate indoor localization technique remains a problem.Dominating in cost of deployment and usability, WiFi RSSI based fingerprinting localization technique is one the most promising technologies today. This paper first gives a detailed explanation about the background, theory and development of this technology and then presents a new WiFi and smart phone based indoor localization method. The work and contribution of the thesis can be summarized as follows:1. This paper gives a detailed research on the characteristics of user body attenuation factor in signal propagation and introduces a new propagation model by adding the factor in the classic log-normal model. Since the existence of user body attenuation phenomenon is decided by user’s orientation, it’s necessary to consider this factor when predicting the signal strength. The new model takes the user’s orientation as a parameter and marks the generated RSSI values with the corresponding orientation. The author suggests clustering the RSSI values with the associated orientation before storing the radio map and sees each cluster as a separate RSSI map generated for this orientation. This strategy can remove the impact in search complexity brought by the new model.2. This paper proposes a new algorithm to trace user’s orientation relying on smart devices’inertial sensors. The algorithm first computes the device’s orientation relative to the horizon by analyzing accelerometer’s reading, and then decides user’s orientation relative to the magnetic field direction with compass sensor.When localizating, the radio map generated for user’s orientation is selected as the search space. Since user’s attenuation factor in RSSI in already considered when generating the radio map, a better localization result is achieved. This paper also presents the implementation of this algorithm using WiFi base stations and android phones. The experiments in the system shows the algorithm can deliver a better localization accuracy.