Observability and Performance Analysis of a Model-Free Synthetic Air Data Estimator
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Observability and Performance Analysis of a Model-Free Synthetic Air Data Estimator
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2019
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Journal of Aircraft
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Article
Abstract
The performance, accuracy, and observability of a model-free angle of attack and angle of sideslip estimator are presented. The estimator does not require an aircraft dynamic model; rather, it only relies on measurements from a GPS receiver, an inertial measurement unit, and a pitot tube. The estimator is an inertial navigation system (INS)/GPS extended Kalman filter augmented with the states to account for wind and an additional measurement from a pitot tube. It is shown that the estimator is conditionally observable. Conditions (maneuvers) that enhance its observability are identified. A bound on the angle of attack and angle of sideslip estimate uncertainties is derived. The effect of INS/GPS, horizontal and vertical wind uncertainty on the accuracy of angle of attack and angle of sideslip estimate is assessed. Simulation and flight-test results of the method are presented. The results show that the 1−σ bound on a small, slow-flying unmanned aerial vehicle for angle of attack and sideslip angle estimates are about 5 and 3 deg, respectively.
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The authors also acknowledge the Minnesota Invasive Terrestrial Plants Center for financial support. The authors would also like to thank NASA (via grant NNX15AV67G), University of Minnesota–The Office of the Vice President for Research–Minnesota’s Discovery, Research, and InnoVation Economy (UMN OVPR MnDRIVE) Initiative, Sentera LLC, and LMCCR Legislature of the State ofMinnesota for supporting this work.
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10.2514/1.C035290
Previously Published Citation
Sun, K., Regan, C. D., & Gebre-Egziabher, D. (2019). Observability and Performance Analysis of a Model-Free Synthetic Air Data Estimator. Journal of Aircraft, 56(4), 1471–1486. https://doi.org/10.2514/1.C035290
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Sun, Kerry; Regan, Christopher D; Gebre-Egziabher, Demoz. (2019). Observability and Performance Analysis of a Model-Free Synthetic Air Data Estimator. Retrieved from the University Digital Conservancy, 10.2514/1.C035290.
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