DocumentCode
1795153
Title
Information fusion distributed navigation for UAVs formation flight
Author
Zhen Ziyang ; Hao Qiushi ; Gao Chen ; Jiang Ju
Author_Institution
Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
fYear
2014
fDate
8-10 Aug. 2014
Firstpage
1520
Lastpage
1525
Abstract
High precision navigation is a key technique for unmanned aerial vehicles (UAVs) formation flight. A methodology for fusing data from inertial navigation system (INS), global positioning system (GPS) and vision sensor is presented. For the lead UAV, a Kalman filter based INS/GPS integrated navigation system is designed. For the wing UAV, a local Kalman filter based INS/GPS integrated subsystem and local Kalman filter based INS/Vision/JTIDS subsystem are designed, and a distributed master filter based on information fusion estimation is designed to get the absolute navigation solution of wing UAV. And then, the relative navigation between the lead UAV and the wing UAV in formation can be obtained. Simulation results verify the validity of this formation navigation architecture for UAVs. Moreover, it illustrates that the distributed information fusion INS/GPS/Vision integrated navigation system for formation UAVs has highest geodetic navigation accuracy, when comparing with INS/GPS integrated navigation system and INS/Vision integrated navigation system.
Keywords
Global Positioning System; Kalman filters; autonomous aerial vehicles; image sensors; inertial navigation; mobile robots; path planning; position control; sensor fusion; telerobotics; INS/GPS integrated subsystem; INS/Vision/JTIDS subsystem; UAV formation flight; distributed information fusion INS/GPS/Vision integrated navigation system; distributed master filter; geodetic navigation accuracy; global positioning system; inertial navigation system; information fusion distributed navigation; information fusion estimation; lead UAV; local Kalman filter; unmanned aerial vehicles; vision sensor; wing UAV; Equations; Global Positioning System; Information filters; Kalman filters; Machine vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location
Yantai
Print_ISBN
978-1-4799-4700-3
Type
conf
DOI
10.1109/CGNCC.2014.7007417
Filename
7007417
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