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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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https://hal-enac.archives-ouvertes.fr/hal-01931087
Contributor : Laurence Porte <>
Submitted on : Thursday, November 22, 2018 - 2:22:26 PM
Last modification on : Wednesday, May 27, 2020 - 2:24:02 PM

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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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