TY - GEN

T1 - Evaluation and Comparison of Different Motion Models for Flight Navigation

AU - Kulemann, Dennis

AU - Jain, Ankit

AU - Schön, Steffen

N1 - Funding Information: This work has been funded by the German Federal Ministry for Economic Affairs and Energy following a resolution of the German Bundestag (project number: 50NA1705). The authors would like to thank Dr. Jens Kremer and Andreas Dach from IGI mbH for conducting the flight experiment with us and providing the reference trajectory solution. Ankit Jain is an associated member of the DFG research training group i.c.sens to which he is really thankful.

PY - 2021/3

Y1 - 2021/3

N2 - Navigation performance of a flight has to be maintained with a certain level of accuracy in civilian or military operations. Global navigation satellite system (GNSS) based devices in flights act as primary source of navigation. In order to improve the accuracy and robustness of the navigation, information from other systems (e.g. IMU) are fused together. The accuracy is further enhanced when adequate motion models are used during the estimation process. In this paper, we present results of multiple motion models in association with aircraft navigation and evaluate their performances. GNSS and inertial measurement unit (IMU) data are recorded in an aerial flight for about three hours. In order to highlight the impact of different motion models, data captured is processed post flight and position estimates are computed with a linearized Kalman filter (LKF). The computed positions are then compared with a reference trajectory and errors are evaluated for all the motion models. For different flight segments, the estimated position root mean square error (RMSE) varies up to a maximum of about 4 decimeters with different motion models. Also, the magnitude of the maximum deviations in highly dynamic maneuvers is reduced by a large extent when compared with different motion models and performance improvement is about 72%.

AB - Navigation performance of a flight has to be maintained with a certain level of accuracy in civilian or military operations. Global navigation satellite system (GNSS) based devices in flights act as primary source of navigation. In order to improve the accuracy and robustness of the navigation, information from other systems (e.g. IMU) are fused together. The accuracy is further enhanced when adequate motion models are used during the estimation process. In this paper, we present results of multiple motion models in association with aircraft navigation and evaluate their performances. GNSS and inertial measurement unit (IMU) data are recorded in an aerial flight for about three hours. In order to highlight the impact of different motion models, data captured is processed post flight and position estimates are computed with a linearized Kalman filter (LKF). The computed positions are then compared with a reference trajectory and errors are evaluated for all the motion models. For different flight segments, the estimated position root mean square error (RMSE) varies up to a maximum of about 4 decimeters with different motion models. Also, the magnitude of the maximum deviations in highly dynamic maneuvers is reduced by a large extent when compared with different motion models and performance improvement is about 72%.

KW - Aircraft navigation

KW - GNSS

KW - IMU

KW - flight experiment

KW - motion models

UR - http://www.scopus.com/inward/record.url?scp=85105456622&partnerID=8YFLogxK

U2 - 10.23919/eucap51087.2021.9411080

DO - 10.23919/eucap51087.2021.9411080

M3 - Conference contribution

SN - 978-1-7281-8845-4

BT - 15th European Conference on Antennas and Propagation, EuCAP 2021

PB - IEEE Computer Society

ER -