Global Positioning Systems, Inertial Navigation, and Integration
Global Positioning Systems, Inertial Navigation, and Integration
Towards adding probabilities and correlations to interval computations
International Journal of Approximate Reasoning
Brief paper: Near optimal interval observers bundle for uncertain bioreactors
Automatica (Journal of IFAC)
Brief paper: Robust set-membership state estimation; application to underwater robotics
Automatica (Journal of IFAC)
Brief paper: Interval observer design for consistency checks of nonlinear continuous-time systems
Automatica (Journal of IFAC)
Brief paper: Interval observers for linear time-invariant systems with disturbances
Automatica (Journal of IFAC)
The extended Kalman filter as an exponential observer for nonlinearsystems
IEEE Transactions on Signal Processing
Optimal interval estimation fusion based on sensor interval estimates with confidence degrees
Automatica (Journal of IFAC)
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In vehicle positioning applications, the confidence level in the position and velocity estimates can be even more significant than accuracy. In this study, a probabilistic interval method is proposed, which combines, through union and intersection operations, the information from a possibly uncertain predictor (the vehicle model) and measurement sensors. The proposed method is compared to Kalman filtering and to guaranteed interval estimation in the context of railway vehicles where security is the key objective.