UAV Tracking based on Unscented Kalman Filter for Sense and Avoid Applications
Siying Wang, Alexander Then, Reinhold Herschel · 2020
In this paper the performance of the Unscented Kalman Filter (UKF) based tracking is investigated for different Sense and Avoid (SAA) flight scenarios. The improvement of the tracking accuracy through integrating the range rate information into the estimation process with UKF is illustrated. The robustness of this method is further evaluated with a data set provided by Airbus, simulating a range of typical approach scenarios with a detection angle of -110° to +110°.