Abstract
The dependence of proposed pedestrian navigation solutions on a dedicated infrastructure is a limiting factor to the deployment of location based services. Consequently self-contained Pedestrian Dead-Reckoning (PDR) approaches are gaining interest for autonomous navigation. Even if the quality of low cost inertial sensors and magnetometers has strongly improved, processing noisy sensor signals combined with high hand dynamics remains a challenge. Estimating accurate attitude angles for achieving long term positioning accuracy is targeted in this work. A new Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ)-based attitude angles estimation filter is proposed and demonstrated with handheld sensors. It benefits from a gyroscope signal modelling in the quaternion set and two new opportunistic updates: magnetic angular rate update (MARU) and acceleration gradient update (AGU). MAGYQ filter performances are assessed indoors, outdoors, with dynamic and static motion conditions. The heading error, using only the inertial solution, is found to be less than 10° after 1.5 km walking. The performance is also evaluated in the positioning domain with trajectories computed following a PDR strategy.
Highlights
The advent of new wearable devices has widened the application field of pedestrian navigation systems and methods
The first innovation is that the Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ)-based attitude and heading estimation filter uses quaternions to parameterize the state vector and the angular rates measurements
The benefit of magnetic angular rate update (MARU) is that it can frequently be applied for bounding the gyroscope errors even in indoor spaces where the Earth magnetic field is disturbed
Summary
The advent of new wearable devices has widened the application field of pedestrian navigation systems and methods. Existing methods [4,5] propose to solve this issue using the accelerations in the navigation frame, which reinforces the critical role of accurate attitude angles estimation in the overall PDR accuracy budget All these factors highlight the critical role of heading estimation in the overall performance of inertial pedestrian navigation solutions with handheld smartphone. The filter takes advantages of the four-dimensional quaternion algebra for reducing the errors introduced by the mathematical representation of rotations and uses a quaternion based state vector It exploits specific states of the measured magnetic field and acceleration vector combined with some hand motions of opportunity for observing the attitude angles and mitigating the sensor errors. A performance analysis of the attitude angles estimation is first conducted and followed by an evaluation in the positioning domain
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