Paper
22 October 2001 WAR HORSE (wide-area reconnaissance: hyperspectral overhead real-time surveillance experiment)
Author Affiliations +
Abstract
In recent years the Optical Sciences Division, Naval Research Laboratory (NRL) has been involved in the development of real-time hyperspectral detection, cueing, target location, and target designation capabilities. Under the Dark HORSE program it was demonstrated that a hyperspectral sensor could be used for the autonomous, real- time detection of airborne and military ground targets. This work has culminated in WAR HORSE, an autonomous real-time visible hyperspectral target detection system that has been configured for us on a Predator Unmanned Air Vehicle (UAV). The sensor system provides Predator with the ability to detect manmade objects in areas of natural background. The system consists of a visible hyperspectral imaging sensor, a real-time signal processor, a high-resolution visible line scan camera, an interface and control software application, and a data storage medium. The system is coupled to an on- board GPS/INS to provide target geo-location information and relevant data is transmitted to a ground station using line- of-sight down-link capabilities. The presented paper will provide an overview of the WAR HORSE sensor system hardware components and their integration aboard a Predator UAV. In addition, the results of a recently completed demonstration aboard the Predator UAV will be provided. This demonstration represents the first autonomous real-time hyperspectral target detection system to flown aboard a Predator UAV.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher M. Stellman, Frederick M. Olchowski, and Joseph V. Michalowicz "WAR HORSE (wide-area reconnaissance: hyperspectral overhead real-time surveillance experiment)", Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); https://doi.org/10.1117/12.445382
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Cited by 25 scholarly publications.
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KEYWORDS
Sensors

Unmanned aerial vehicles

Hyperspectral target detection

Human-machine interfaces

Scanners

Image analysis

Image sensors

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