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A shadow detection and extraction algorithm using digital elevation models and x‐band weather radar measurements

, &
Pages 1531-1549 | Received 06 Feb 2004, Accepted 30 Sep 2004, Published online: 22 Feb 2007
 

Abstract

The aviation industry has been investigating the potential of synthetic and enhanced vision systems (SVS and EVS) to increase the situational awareness of pilots who are operating in low‐visibility weather conditions. Synthetic vision displays provide a real‐time depiction of a terrain model from the pilot's perspective. To ensure the integrity of this terrain depiction, consistency checking using remote sensing of the terrain environment has been suggested. This requires the detection and extraction of terrain features from both the model and the sensor measurements. Further, the features must be represented in the same reference domain.

Terrain shadowing occurs when areas are not in the line‐of‐sight of the observer. It is these shadowed regions and their morphological characteristics that are identified as the feature domain in which consistency can be assessed between two sources of terrain information. This paper describes an algorithm to extract shadow features from digital elevation models during flight to enable direct comparison with x‐band radar modus operandi. Results are presented using flight‐test data acquired from two platforms with different radar equipment.

The proposed algorithm not only has application to the consistency‐checking problem, but also to terrain navigation, image fusion, and digital elevation model accuracy assessments.

Acknowledgments

The authors would like to thank the Ohio University King Air C90 flight crew and the DC‐8 flight crew from NASA's Dryden Flight Research Center. Jonathon Sayre's efforts at Ohio University developing the WxR data collection software and hardware is also very much appreciated. Donna Gallaher from NASA Langley Research Center led the equipment installation activities on the DC‐8, her talents and dedication are to be commended as well.

The work presented in this paper was supported through the NASA Langley Research Center under Cooperative Agreement NCC‐1‐351.

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