Indoor Mobile Localization Based on A Tightly Coupled UWB/INS Integration

A growing research effort has been dedicated to indoor localization specifically the integration of multiple local positioning techniques, allowing to profit from their advantages. However, integration methods that rely mainly on practicable measurement models or algorithm efficiency. This paper proposes a tightly coupled UWB/INS method for indoor pedestrian applications. In indoor environments, wireless signal outage and severe multipath propagation very often lead to large ranging errors and make Ultra-Wide Band (UWB) based localization barely possible. On the other hand, Micro-Electro-Mechanical System (MEMS) Inertial Navigation System (INS) is necessary to conquer its constant bias, drift, and accumulated errors with time. Based on the characteristics of UWB and inertial measurements, a loosely coupled model using an Extended Kalman Filter (EKF) and a tightly coupled model using another EKF are put forward, which aims to reduce the accumulated error and multipath effects for the indoor mobile tracking. The experiment results demonstrate that, when compared with the accuracy of UWB, the combination of UWB/INS increases by 60.61% with the tight integration model and 31.47% with the loose integration.