Vehicle attitude estimation is nowadays essential for a wide range of applications, e.g. guidance of unmanned vehicles, robotics and automotive controls. In this paper, the attitude estimation problem is solved by means of a velocity-aided, Extended Kalman Filter with correlated noise (CEKF), exploiting the intrinsic correlation between sensor noise in a velocity-aided model. Reconstruction of a motorcycle attitude is considered as a use case. The problem is addressed in a simulation scenario under noisy measurements. Performance of the CEKF is compared to that of the classic EKF formulation by evaluating the RMS of the reconstruction error.

Velocity aided, correlated noise extended kalman filtering for attitude estimation: A motorcycle case study

Bruschetta M.;Caiaffa L.;Picotti E.;Beghi A.
2021

Abstract

Vehicle attitude estimation is nowadays essential for a wide range of applications, e.g. guidance of unmanned vehicles, robotics and automotive controls. In this paper, the attitude estimation problem is solved by means of a velocity-aided, Extended Kalman Filter with correlated noise (CEKF), exploiting the intrinsic correlation between sensor noise in a velocity-aided model. Reconstruction of a motorcycle attitude is considered as a use case. The problem is addressed in a simulation scenario under noisy measurements. Performance of the CEKF is compared to that of the classic EKF formulation by evaluating the RMS of the reconstruction error.
2021
2021 29th Mediterranean Conference on Control and Automation, MED 2021
29th Mediterranean Conference on Control and Automation, MED 2021
978-1-6654-2258-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3402068
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