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• W3216653531 startingPage "107237" @default.
• W3216653531 abstract "This article proposes an inertial navigation algorithm intended to lower the negative consequences of the absence of GNSS (Global Navigation Satellite System) signals on the navigation of autonomous fixed wing low SWaP (Size, Weight, and Power) UAVs (Unmanned Air Vehicles). In addition to accelerometers and gyroscopes, the filter takes advantage of sensors usually present onboard these platforms, such as magnetometers, Pitot tube, and air vanes, and aims to minimize the attitude error and reduce the position drift (both horizontal and vertical) with the dual objective of improving the aircraft GNSS-Denied inertial navigation capabilities as well as facilitating the fusion of the inertial filter with visual odometry algorithms. Stochastic high fidelity Monte Carlo simulations of two representative scenarios involving the loss of GNSS signals are employed to evaluate the results, compare the proposed filter with more traditional implementations, and analyze the sensitivity of the results to the quality of the onboard sensors. The author releases the C++ implementation of both the navigation filter and the high fidelity simulation as open-source software." @default.
• W3216653531 created "2021-12-06" @default.
• W3216653531 creator A5033322846 @default.
• W3216653531 creator A5039941153 @default.
• W3216653531 date "2022-01-01" @default.
• W3216653531 modified "2023-09-30" @default.
• W3216653531 title "Reduction of GNSS-Denied inertial navigation errors for fixed wing autonomous unmanned air vehicles" @default.
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• W3216653531 doi "https://doi.org/10.1016/j.ast.2021.107237" @default.
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