Research On Indoor Localization Based On Fusion Of Multi-source Information

With the rapid development of mobile network and the popularization of intelligent terminals, localization based service has received more and more wide applications. GPS has been widely used in outdoor environment. As the supplement of the GPS, indoor localization has also attracted increasing research attentions. Existing indoor localization technologies include Bluetooth, UWB and so on; however, these methods all rely on the infrastructure built in advance, which increases the cost of localization.At present, Micro Electro Mechanical System (MEMS) has been almost equipped in every mobile intelligent terminal. MEMS is not only able to obtain the feature information of the environment, such as magnetic field intensity and barometric pressure, but also the motion state of the user. Among the indoor localization technology using information from MEMS, the method of geomagnetic matching can work well. However, the traditional method of geomagnetic matching does not fully utilize the feature information of the geomagnetic field; meanwhile, the motion state of the user is also neglected. At the same time, localization technology based on inertial sensors can provide the motion state of the user, but cannot estimate the initial state of user localization. Therefore, we shall combine both methods in this work, such that the advantages can be fully utilized. Based on this idea, we can implement an indoor localization method which is reliable and infrastructure-free. Firstly, this thesis analyzes the feature of geomagnetic field through experiments, and shows that the magnetic field is suitable for localization. Secondly, we describe principle of the indoor localization system combining the geomagnetic matching with inertial sensors. To further enhance the performance of the algorithm, we modify the traditional particle filter, which could increase the diversity of the particles and make the system more robust.After the simulation results show that the algorithm works well, we implement a prototype system on smart pone based on the proposed method. We analyze the scenario with multiple users requiring localization services, where a cooperative localization algorithm is proposed to further fuse the distance information between users. The performance ofthe algorithm is verified through simulation.