Paper
19 June 2014 Identifying opportune landing sites in degraded visual environments with terrain and cultural databases
Marc Moody, Robert Fisher, J. Kristin Little
Author Affiliations +
Abstract
Boeing has developed a degraded visual environment navigational aid that is flying on the Boeing AH-6 light attack helicopter. The navigational aid is a two dimensional software digital map underlay generated by the Boeing™ Geospatial Embedded Mapping Software (GEMS) and fully integrated with the operational flight program. The page format on the aircraft’s multi function displays (MFD) is termed the Approach page. The existing work utilizes Digital Terrain Elevation Data (DTED) and OpenGL ES 2.0 graphics capabilities to compute the pertinent graphics underlay entirely on the graphics processor unit (GPU) within the AH-6 mission computer. The next release will incorporate cultural databases containing Digital Vertical Obstructions (DVO) to warn the crew of towers, buildings, and power lines when choosing an opportune landing site. Future IRAD will include Light Detection and Ranging (LIDAR) point cloud generating sensors to provide 2D and 3D synthetic vision on the final approach to the landing zone. Collision detection with respect to terrain, cultural, and point cloud datasets may be used to further augment the crew warning system. The techniques for creating the digital map underlay leverage the GPU almost entirely, making this solution viable on most embedded mission computing systems with an OpenGL ES 2.0 capable GPU. This paper focuses on the AH-6 crew interface process for determining a landing zone and flying the aircraft to it.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marc Moody, Robert Fisher, and J. Kristin Little "Identifying opportune landing sites in degraded visual environments with terrain and cultural databases", Proc. SPIE 9087, Degraded Visual Environments: Enhanced, Synthetic, and External Vision Solutions 2014, 90870M (19 June 2014); https://doi.org/10.1117/12.2052835
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KEYWORDS
Visualization

Clouds

Databases

LIDAR

OpenGL

3D vision

Buildings

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