Integrated Multi-Sensor State Estimation Using GNSS and Redundant IMUs for UAVs Beyond Visual Line of Sight

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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 languageEnglish
Title of host publication2019 European Navigation Conference (ENC)
ISBN (Electronic)978-1-5386-9473-2
DOIs
Publication statusPublished - 2019

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State estimation
Unmanned aerial vehicles (UAV)
Barometers
Gyroscopes
Sensors
Extended Kalman filters
Magnetometers
Accelerometers
Global positioning system
Navigation
Aircraft

Cite this

Integrated Multi-Sensor State Estimation Using GNSS and Redundant IMUs for UAVs Beyond Visual Line of Sight. / Reitbauer, Eva Maria.

2019 European Navigation Conference (ENC). 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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