Inertial Pocket Navigation System for Pedestrians

Abstract

There is nowadays a high demand of pedestrian navigation systems, which are integrated in safety-of-life Services such as disaster management for rescue personnel or locationbased services such as guidance in hospitals, airports or shopping malls. In this thesis, indoor and urban environments constitute the targeted scenarios and the navigation is performed with inertial and magnetic sensors due to their wide availability, light-weight and infrastructure-less nature. The research of this thesis aims at improving or covering specific gaps of pedestrian navigation areas to offer versatile pedestrian navigation systems for a wide range of applications. First, the use of magnetic field measurements to compensate the error of the gyroscopes and their effect on the estimated orientation has been comprehensibly analyzed. Quasi-error-free measurements with known bias values have been used combined with different magnetic field distributions and the results have been endorsed with medium-cost sensors' measurements. It is concluded that the use of magnetic measurements is beneficial to estimate the bias of the gyroscopes, yielding to reduced orientation estimation errors. However, the targeted scenarios commonly present perturbed magnetic fields and the biases' estimation process becomes prohibitively slow. Second, several algorithms have been proposed in this thesis that outperform the accuracy of the horizontal displacement estimation with respect to the state of the art. Additionally, an innovative vertical displacement estimation algorithm has been proposed and tested in real-world scenarios. This algorithm makes it possible for the first time to solve unaided 3D inertial navigation for non-shoe-mounted sensors. Lastly, a novel drift estimation algorithm capable of preventing positioning errors caused by orientation errors is proposed. The computation of the drift error is based on landmarks seamlessly detected using solely inertial measurements. Landmarks defining the building or City layout have been chosen to be stairs and corners. By re visiting these landmarks it is possible to compute the accumulated drift error, which is used to reduce the orientation error. The proposed algorithm has been extensively tested with quasi-error-free and medium-cost sensors' measurements. Two types of corrections, online and post-processed, are presented to adapt the pedestrian navigation system to the particular application.