Performance Comparison between EKF and UKF in GPS/INS Low Observability Conditions

For the UAV localization problem, GPS-IMU-based sensor fusion is widely used. In such combination, GPS could correct IMU drift error and IMU could compensate for a low sampling rate of GPS. However, it is known that the GPS-IMU system becomes unobservable for a certain type of maneuver, e.g. hoverin...

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Bibliographic Details
Main Authors: Ryu, Kyunghyun, Kang, Jiseock, Lee, Dongjun
Format: Conference Proceeding
Language:English
Subjects:
Autonomous aerial vehicles
Estimation
Global positioning system (GPS)
GPS/INS
Gyroscopes
Inertial navigation
Kalman filter
Location awareness
Navigation
Observability
Orbits
Sensor fusion
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Summary:For the UAV localization problem, GPS-IMU-based sensor fusion is widely used. In such combination, GPS could correct IMU drift error and IMU could compensate for a low sampling rate of GPS. However, it is known that the GPS-IMU system becomes unobservable for a certain type of maneuver, e.g. hovering as the simplest instance. This paper presents a comparison of two variations of Kalman filter, extended Kalman filter (EKF) and unscented Kalman filter (UKF) for unmanned aerial vehicle (UAV) localization problem in such low observability maneuver. Observability analysis and simulation are conducted on various maneuvers including constant attitude motions and orbit motion. This comparison could help the localization algorithm decision in the development of the UAV system.
ISSN:2642-3901
DOI:10.23919/ICCAS52745.2021.9649748