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Nonlinear Kalman Filter for Multi-Sensor Navigation of Unmanned Aerial Vehicles: Application to Guidance and Navigation of Unmanned Aerial Vehicles Flying in a Complex Environment

Abstract : Nonlinear Kalman Filter for Multi-Sensor Navigation of Unmanned Aerial Vehicles covers state estimation development approaches for Mini-UAV. The book focuses on Kalman filtering technics for UAV design, proposing a new design methodology and case study related to inertial navigation systems for drones. Both simulation and real experiment results are presented, thus showing new and promising perspectives. Gives a state estimation development approach for mini-UAVs Explains Kalman filtering techniques Introduce a new design method for unmanned aerial vehicles Introduce cases relating to the inertial navigation system of drones
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Ouvrage (y compris édition critique et traduction)
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https://hal-enac.archives-ouvertes.fr/hal-01931087
Contributeur : Laurence Porte Connectez-vous pour contacter le contributeur
Soumis le : jeudi 22 novembre 2018 - 14:22:26
Dernière modification le : mercredi 3 novembre 2021 - 05:17:12

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  • HAL Id : hal-01931087, version 1

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Jean-Philippe Condomines. Nonlinear Kalman Filter for Multi-Sensor Navigation of Unmanned Aerial Vehicles: Application to Guidance and Navigation of Unmanned Aerial Vehicles Flying in a Complex Environment. ISTE Press, 2018, 978-1785482854. ⟨hal-01931087⟩

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