The Bayesian Neural Kalman Filter uses a trained BNN to predict UAV states and uncertainties, then applies a Kalman update to outperform standard EKF and UKF on synthetic data under high noise and low sampling rates.
Iden- tification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter
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Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments
The Bayesian Neural Kalman Filter uses a trained BNN to predict UAV states and uncertainties, then applies a Kalman update to outperform standard EKF and UKF on synthetic data under high noise and low sampling rates.