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Heading drift error remains a problem in a standalone navigation system that uses only low cost MEMS IMU due to yaw error unobservability. This paper therefore proposes a shoe mounted IMU approach, integrated with ZUPT and building heading information in Kalman filter environment to reduce heading drift for pedestrian navigation application. There were no(More)
Modern smartphones contain a number of sensors that can be used for navigation when GPS signals are unavailable. Low cost MEMS gyros and accelerometers are increasingly becoming available in modern devices, however when used for positioning, they typically result in large errors after very short periods of time. This paper investigates using measurements(More)
In environments where GNSS is unavailable or not useful for positioning, the use of low cost MEMS-based inertial sensors has paved a way to a more cost effective solution. Of particular interest is a foot mounted pedestrian navigation system, where zero velocity updates (ZUPT) are used with the standard strapdown navigation algorithm in a Kalman filter to(More)
This paper proposes an integration of ‘building heading’ information with ZUPT in a Kalman filter, using a shoe mounted IMU approach. This is done to reduce heading drift error, which remains a major problem in a standalone shoe mounted pedestrian navigation system. The standalone system used in this paper consists of only single low cost MEMS IMU that(More)
Pedestrian navigation especially indoors suffers from the unavailability of useful GNSS signals for positioning. Alternatively, a low-cost Inertial Measurement Unit (IMU) positioning system that does not depend on the GNSS signal can be used for indoor navigation. However its performance is still compromised because of the fastaccumulating heading drift(More)
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