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Abstract
This paper proposes a filter architecture which incorporates accelerometer and gyroscope measurements from redundant IMUs into the state estimation of UAVs. A loosely coupled, federated extended Kalman filter combining Galileo, GPS, barometer, magnetometer and measurements from two IMUs is presented. A navigation sensor configuration for a UAV of class 2 will be presented. The proposed filter algorithm and the sensor configuration are tested and validated using an ultralight aircraft equipped with highly precise reference equipment. This paper concludes with an analysis of the achievable accuracy and the improvements made by using both IMUs for the state estimation.
Original language | English |
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Title of host publication | 2019 European Navigation Conference (ENC) |
ISBN (Electronic) | 978-1-5386-9473-2 |
DOIs | |
Publication status | Published - 2019 |
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Dive into the research topics of 'Integrated Multi-Sensor State Estimation Using GNSS and Redundant IMUs for UAVs Beyond Visual Line of Sight'. Together they form a unique fingerprint.Activities
- 1 Talk at conference or symposium
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Integrated Multi-Sensor State Estimation Using GNSS and Redundant IMUs for UAVs Beyond Visual Line of Sight
Eva Maria Reitbauer (Speaker)
9 Apr 2019 → 12 Apr 2019Activity: Talk or presentation › Talk at conference or symposium › Science to science