Abstract
This paper presents an integrated navigation tool developed in the framework of an advanced study on navigation of Unmanned Aerial Vehicles. The study aimed at testing innovative navigation sensor configurations to support fully autonomous flight even during landings and other critical mission phases. The tool is composed of sensor simulation and data fusion software. The most important navigation sensors that are installed onboard an unmanned aircraft have been modeled: i.e. inertial, GPS, air data, high accuracy altimeter, and magnetometer. Their model included every non negligible error source that has been documented in the literature. Moreover, a specific sensor data fusion algorithm has been developed that integrates inertial sensor measurements with GPS and radar altimeter measurements. The paper reports on numerical testing of sensor simulator and data fusion algorithm. The algorithm was coded for real time implementation to perform hardware–in-the-loop validation and in flight tests onboard a small Unmanned Aerial Vehicle.
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Esposito, F., Accardo, D., Moccia, A., Ciniglio, U., Corraro, F., Garbarino, L. (2007). Real-Time Simulation and Data Fusion of Navigation Sensors for Autonomous Aerial Vehicles. In: Elleithy, K. (eds) Advances and Innovations in Systems, Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6264-3_24
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DOI: https://doi.org/10.1007/978-1-4020-6264-3_24
Publisher Name: Springer, Dordrecht
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