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Proceedings Paper

Sensor classification and obstacle detection for aircraft external hazard monitoring
Author(s): Mark Smearcheck; Ananth K. Vadlamani; Maarten Uijt de Haag
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Paper Abstract

This paper introduces a sensor-modeling framework to support the test and evaluation of External Hazard Monitor configurations and algorithms within the Intelligent Integrated Flight Deck (IIFD). The paper, furthermore, examines various runway hazards that may be encountered during aircraft approach procedures and classifies sensors that are suited to detect these hazards. The work performed for this research is used to evaluate sensing technologies to be implemented in the IIFD, a key component of NASA's Next Generation Air Transportation System. To detect objects on or near airport runways, an aircraft will be equipped with a monitoring system that interfaces to one or more airborne remote sensors and is capable of detection, classification, and tracking of objects in varying weather conditions. Physical properties of an object such as size, shape, thermal signature, reflectivity, and motion are considered when evaluating the sensor most suitable for detecting a particular object. The results will be used to assess the threat level associated with the objects in terms of severity and risk using statistical methods based on the sensor's measurement and detection capabilities. The sensors being evaluated include, airborne laser range scanners, forward looking infrared (FLIR), three dimensional imagers, and visible light cameras.

Paper Details

Date Published: 15 April 2008
PDF: 12 pages
Proc. SPIE 6957, Enhanced and Synthetic Vision 2008, 69570F (15 April 2008); doi: 10.1117/12.784524
Show Author Affiliations
Mark Smearcheck, Ohio Univ. (United States)
Ananth K. Vadlamani, Ohio Univ. (United States)
Maarten Uijt de Haag, Ohio Univ. (United States)


Published in SPIE Proceedings Vol. 6957:
Enhanced and Synthetic Vision 2008
Jeff J. Güell; Maarten Uijt de Haag, Editor(s)

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