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Nonlinear kalman filtering for multi...

Condomines, Jean-Philippe,

Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehiclesapplication to guidance and navigation of unmanned aerial vehicles flying in a complex environment /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehiclesJean-Philippe Condomines.
Reminder of title:	application to guidance and navigation of unmanned aerial vehicles flying in a complex environment /
Author:	Condomines, Jean-Philippe,
Published:	Amsterdam :Elsevier,2018.
Description:	1 online resource :ill. (some col.)
Subject:	Drone aircraft.
Online resource:	https://www.sciencedirect.com/science/book/9781785482854
ISBN:	9780081027448 (electronic bk.)

Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehiclesapplication to guidance and navigation of unmanned aerial vehicles flying in a complex environment /
Condomines, Jean-Philippe,

Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehiclesapplication to guidance and navigation of unmanned aerial vehicles flying in a complex environment /[electronic resource] :Jean-Philippe Condomines. - Amsterdam :Elsevier,2018. - 1 online resource :ill. (some col.)

Includes bibliographical references and index.

Nonlinear Kalman Filtering 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.

ISBN: 9780081027448 (electronic bk.)Subjects--Topical Terms:

337979
Drone aircraft.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: TL685.35

Dewey Class. No.: 623.7469

Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehiclesapplication to guidance and navigation of unmanned aerial vehicles flying in a complex environment /
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520 $a Nonlinear Kalman Filtering 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.
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