Unscented Kalman Filter for INS/GNSS Data Fusion with Time Delay
Kanishke Gamagedara, Taeyoung Lee, Murray R. Snyder · AIAA AVIATION 2021 FORUM · 2021
View Video Presentation: https://doi.org/10.2514/6.2021-2486.vid This paper presents an estimation scheme for an unmanned aerial vehicle (UAV) operating around a Navy research vessel in ocean environments. Estimating the accurate position of a UAV relative to a ship is critical for airborne measurements of ship air wake and autonomous close-proximity flights. However, the position measurements from a low-cost real-time kinematics (RTK) GPS system or vision-based localization often suffer from time-delays caused by communication overload or associated computation. In this paper, an unscented Kalman filter is developed to integrate time-delayed relative position measurements with non-delayed inertial measurements to accurately estimate the position and the attitude of a UAV relative to a ship. The proposed approach is composed of correction with the delayed measurement and forward-propagation to the current time. The efficacy of the proposed scheme is illustrated by a numerical example.