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- W2325367996 abstract "*† ‡ § This paper describes the development of a Modular Avionics Platform (MAP) by researchers at West Virginia University. The purpose of the MAP architecture is to fulfill the avionic needs for a variety of UAV-based flight research program at academic institutions and research organizations. A miniaturized autopilot system plays a central role in the MAP architecture by not only providing basic waypoint navigation and fail-safe functionalities, but also acting as a central hub for interfacing with various Commercial-OffThe-Shelf (COTS) sensors, communications, and computational resources. Since size, weight, and power-consumption are critical issues for the design of miniaturized autopilot systems, sensor fusion algorithms are required to provide an adequate level of attitude reference for control and navigation purposes. A computationally efficient algorithm based on an Extended Kalman Filter (EKF) is developed and validated using actual UAV flight data. The comparison with data from a high quality vertical gyro measurement shows satisfactory performance for the sensor fusion algorithm." @default.
- W2325367996 created "2016-06-24" @default.
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- W2325367996 date "2008-06-15" @default.
- W2325367996 modified "2023-10-05" @default.
- W2325367996 title "Integrated Avionics System for Research UAVs" @default.
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- W2325367996 doi "https://doi.org/10.2514/6.2008-7490" @default.
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