Joint Estimation of Carrier Airwake and Aircraft Dynamics Using Invariant Extended Kalman Filter

This paper presents a novel state estimator for carrier-based aircraft that utilizes the theory of invariant observers. By integrating the carrier-based aircraft's position, attitude, velocity, and wind speed onto the Lie group, the proposed estimator can combine information from sensors such as the pitot tube and IMU, and use the Right-Invariant Extended Kalman Filter to provide accurate and real-time estimates of the aircraft's attitude, speed, and wind speed during landing. To further enhance estimation accuracy, information from the GNSS is incorporated, and the state variables are estimated using a robust and accurate Left-Invariant Extended Kalman Filter. The use of a federated filtering approach to combine the estimation results from different sensors enhances the accuracy and reliability of the estimation results. The effectiveness of the proposed estimation method is demonstrated through a detailed theoretical analysis, while extensive simulation experiments validate its superior performance.