Smartphone Orientation Tracking Algorithm for Pedestrian Navigation

Maan E. Khedr, and Naser El-Sheimy

Peer Reviewed

Abstract: Navigation has become an essential service for many of our day-today activities. Nowadays and with widespread integration of sensor in consumer device, indoor pedestrian navigation relies on the use of the Inertial Navigation Systems (INS) by using the inertial sensors allocated in smart devices such as smartphones. INS-based navigation is a relative navigation solution that requires the knowledge of an initial state, upon which the inertial measurements are used over time to determine the current navigation state relative to the initial state. Alignment tracking between the users’ body – which is not the same as the sensor – frame and the navigation frame is a key challenge for INS to be able to obtain an accurate navigation solution. Errors in alignment tend to cause huge errors in the navigation state in two aspects: total distance traveled, and direction of motion. The error in distance traveled arises from wrong leveling of the measurements from the body frame to the navigation frame, hence horizontal measurements are poised by a fraction of the gravity component that accumulates over time and makes the position estimate drift drastically from the true position. This paper presents an algorithm for tracking the device orientation changes with respect to the pedestrian. The algorithm works on estimating the tilt angles – roll and pitch – between the body and navigation frames on an epoch-by-epoch basis. It also estimates the transformed forces from the body frame into an intermediate frame between the body and navigation. The intermediate frame proposed is a leveled frame with the navigation, but with different heading from it. The walking direction in the horizontal plane of the intermediate frame represents the difference in heading between the pedestrian and the device. This algorithm is proposed as a part of a full Pedestrian Dead Reckoning (PDR) framework, and is required for the step detection phase and step length estimation process.
Published in: Proceedings of the 2017 International Technical Meeting of The Institute of Navigation
January 30 - 2, 2017
Hyatt Regency Monterey
Monterey, California
Pages: 105 - 115
Cite this article: Khedr, Maan E., El-Sheimy, Naser, "Smartphone Orientation Tracking Algorithm for Pedestrian Navigation," Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, January 2017, pp. 105-115.
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