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    Relative Heading Estimation for Pedestrians Based on the Gravity Vector

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    1923948.pdf (1.212Mb)
    Date
    2021-03-15
    Author
    Thio, Vincent
    Ånonsen, Kjetil Bergh
    Bekkeng, Jan Kenneth
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    Abstract
    Inertial navigation of pedestrians carrying a smart device is a core component of many indoor positioning systems. While infrastructure-based solutions typically depend on an installation of dedicated hardware, inertial navigation depends only on sensors embedded in the device itself. A single solution can thus be applied to a large range of use cases. This work focuses on one of the main challenges in inertial navigation: user heading estimation. We describe a complete statistical model for heading estimation based on the IMU and magnetometer, assuming a fixed device pose on the pedestrian. Our aim is to provide a stand-alone solution, suitable for direct implementation into a larger positioning framework. The method consists of two consecutive parts. The first focuses on gravity vector estimation based on IMU data. We describe a method for obtaining independent estimates under dynamic conditions, thereby removing the quasi-static initialization phase required by conventional methods. The second part combines the gravity vector with gyro and magnetic measurements to estimate user heading. The proposed method is tested against a motion capture system, and against an alternative method based on attitude. We find that both methods produce similar results in terms of accuracy.
    URI
    http://hdl.handle.net/20.500.12242/2987
    DOI
    10.1109/JSEN.2021.3052430
    Description
    Relative Heading Estimation for Pedestrians Based on the Gravity Vector. IEEE Sensors Journal 2021 ;Volum 21.(6) s. 8218-8225
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