A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

2004 ◽  
Author(s):  
Michael D. Byrne ◽  
Alex Kirlik ◽  
Michael D. Fleetwood ◽  
David G. Huss ◽  
Alex Kosorukoff ◽  
...  
Keyword(s):  
Closed Loop ◽  
Vision System ◽  
Modeling Approach ◽  
Synthetic Vision

A Closed-Loop, Act-R Approach to Modeling Approach and Landing with and without Synthetic Vision System (SVS) Technology

2004 ◽  
Vol 48 (17) ◽  
pp. 2111-2115 ◽  
Author(s):  
Michael D. Byrne ◽  
Alex Kirlik ◽  
Michael D. Fleetwood ◽  
David G. Huss ◽  
Alex Kosorukoff ◽  
...  
Keyword(s):  
Closed Loop ◽  
Vision System ◽  
Modeling Approach ◽  
Synthetic Vision

scholarly journals An Efficient Synthetic Vision System for 3D Multi-character Systems

2003 ◽  
pp. 356-357 ◽  
Author(s):  
Miguel Lozano ◽  
Rafael Lucia ◽  
Fernando Barber ◽  
Fran Grimaldo ◽  
Antonio Lucas ◽  
...  
Keyword(s):  
Vision System ◽  
Synthetic Vision

Hybrid enhanced and synthetic vision system architecture for rotorcraft operations

2002 ◽  
Author(s):  
Norah K. Link ◽  
Ronald V. Kruk ◽  
David McKay ◽  
Sion A. Jennings ◽  
Greg Craig
Keyword(s):  
System Architecture ◽  
Vision System ◽  
Synthetic Vision

Alaskan flight trials of a synthetic vision system for instrument landings of a piston twin aircraft

1999 ◽  
Author(s):  
Andrew K. Barrows ◽  
Keith W. Alter ◽  
Chad W. Jennings ◽  
J. D. Powell
Keyword(s):  
Vision System ◽  
Synthetic Vision

Flight tests with enhanced/synthetic vision system for rescue helicopter

2011 ◽  
Author(s):  
Hiroka Tsuda ◽  
Kohei Funabiki ◽  
Tomoko Iijima ◽  
Kazuho Tawada ◽  
Takashi Yoshida
Keyword(s):  
Vision System ◽  
Flight Tests ◽  
Rescue Helicopter ◽  
Synthetic Vision

scholarly journals Fusion of Enhanced and Synthetic Vision System Images for Runway and Horizon Detection

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3802 ◽  
Author(s):  
Ahmed F. Fadhil ◽  
Raghuveer Kanneganti ◽  
Lalit Gupta ◽  
Henry Eberle ◽  
Ravi Vaidyanathan
Keyword(s):  
Wavelet Transform ◽  
Flight Control ◽  
Vision System ◽  
Discrete Wavelet ◽  
Fusion Rules ◽  
Synthetic Vision ◽  
Signal Fusion ◽  
Fusion Applications ◽  
Image Pairs ◽  
Poor Lighting

Networked operation of unmanned air vehicles (UAVs) demands fusion of information from disparate sources for accurate flight control. In this investigation, a novel sensor fusion architecture for detecting aircraft runway and horizons as well as enhancing the awareness of surrounding terrain is introduced based on fusion of enhanced vision system (EVS) and synthetic vision system (SVS) images. EVS and SVS image fusion has yet to be implemented in real-world situations due to signal misalignment. We address this through a registration step to align EVS and SVS images. Four fusion rules combining discrete wavelet transform (DWT) sub-bands are formulated, implemented, and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and pairs containing simulated turbulence. Evaluations reveal that runways and horizons can be detected accurately even in poor visibility. Furthermore, it is demonstrated that different aspects of EVS and SVS images can be emphasized by using different DWT fusion rules. The procedure is autonomous throughout landing, irrespective of weather. The fusion architecture developed in this study holds promise for incorporation into manned heads-up displays (HUDs) and UAV remote displays to assist pilots landing aircraft in poor lighting and varying weather. The algorithm also provides a basis for rule selection in other signal fusion applications.

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