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CEAS EuroGNC 2019 |
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A Robust Complementary Filter Approach for Attitude Estimation of Unmanned Aerial Vehicles using AHRS |
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| Abstract: Most attitude filters utilise the accelerometer as a vector measurement of gravity to estimate pitch and roll angles; however, during accelerated flight, this assumption does not hold. This paper develops a robust attitude filter model that determines when the accelerometers can be used as vector measurements by using a time-dependent model of steadiness. Furthermore, a gyro measurement model is developed using a Gaussian random walk model as the basis for bounding bias estimates and rejecting improbable estimates that arise from slow dynamics or transitioning from steady to dynamic motion. Monte-Carlo simulations using test cases with dynamic motion were performed to verify its performance. The bias is accurately tracked and gyro integration performance during unsteady motion ultimately improved. Moreover, roll dynamics were tracked more accurately than current state-of-the-art complementary filters. | ||||||
| Keywords: Inertial navigation; Mini/Micro air vehicles; Sensor fusion | ||||||
 View PDF CEAS-GNC-2019-036 |
| Johann Meyer, Kreelan Padayachee, Benjamin A. Broughton: A Robust Complementary Filter Approach for Attitude Estimation of Unmanned Aerial Vehicles using AHRS. Proceedings of the 2019 CEAS EuroGNC conference. Milan, Italy. April 2019. CEAS-GNC-2019-036. |
| BibTeX entry: @Incollection{CEAS-GNC-2019-036, authors = {Meyer, Johann and Padayachee, Kreelan and Broughton, Benjamin A.}, title = {A Robust Complementary Filter Approach for Attitude Estimation of Unmanned Aerial Vehicles using {AHRS}}, booktitle = {Proceedings of the 2019 {CEAS EuroGNC} conference}, address = {Milan, Italy}, month = apr, year = {2019}, note = {CEAS-GNC-2019-036} } |