[time]
2023-08-29T11:00:12+02:00

[track]
4

[team_name]
VINF

[team_institution]
Institute for Sensing and Navigation, Shanghai Jiao Tong University

[logolink]


[team_members]
Jiale Han, Maoran Zhu, Yuanxin Wu

[reference_person]
Jiale Han

[reference_email]
hanjl2022@sjtu.edu.cn

[description_short]
    In our system design, the core is an information fusion algorithm based on the Error State Kalman Filter with five constraints, including the Zero-velocity update (ZUPT), the Zero angular rate update (ZARU), the Improved heuristic drift elimination (iHDE), the Ellipsoid constraint, and the Constant speed.
    Additionally, the height variation calculated by the pressure sensor can also be used to correct the navigation state. The magnetic field will be used for loop detection, enabling the utilization of historical estimated positions to correct the current navigation state. When the user comes to an outdoor scene, the received GNSS signals will be used to correct the current navigation state.
    The parameters of inertial sensors, such as the bias instability of gyroscopes and accelerometers, the angle random walk, and the velocity random walk, are determined through long-term static data. 

[description_long_link]
https://github.com/zzzwa66/IPIN/blob/main/Technical Description.pdf

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