Pose estimation is a critical problem in autonomous vehicle navigation, especially in circumstances involving sensor failures or attacks. In this chapter, a filter‐based secure dynamic pose estimation approach is introduced such that the vehicle pose can be resilient under possible sensor attacks. Our proposed estimator coincides with the conventional Kalman filter when all sensors on autonomous vehicles are benign. If fewer than half of the measurement states consist of randomly occurring deception attacks, this chapter still gives stable estimates of the pose states: i.e. an upper bound for the estimation error covariance is guaranteed. Pose estimation results with single and multiple attacks on the testing route validate the effectiveness and robustness of the proposed approach.
Filter‐Based Secure Dynamic Pose Estimation
27.09.2022
21 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
SECURE POSE ESTIMATION FOR AUTONOMOUS VEHICLES UNDER CYBER ATTACKS
British Library Conference Proceedings | 2019
|THE BINGHAM-GAUSS MIXTURE FILTER FOR POSE ESTIMATION
British Library Conference Proceedings | 2016
|The Bingham-Gauss Mixture Filter for Pose Estimation
AIAA | 2016
|