Paper
29 April 2010 Trace detection of explosives using an in-line high-volume sampler, preconcentrator, and Fido explosives detector
Russ Ingram, John Sikes
Author Affiliations +
Abstract
This paper shall demonstrate the results of a prototype system to detect explosive objects and obscured contaminated targets. By combining a high volume sampling nozzle with an inline 2-stage preconcentrator and a Fido, greater standoff is achieved than with the Fido alone. The direct application of this system is on the Autonomous Mine Detection System (AMDS) but could be deployed on a large variety of robotic platforms. It is being developed under the auspices of the U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate, Countermine Division. This device is one of several detection tools and technologies to be used on the AMDS. These systems will have multiple, and at times, overlapping objectives. One objective is trace detection on the surface of an unknown potential target. By increasing the standoff capabilities of the detector, the fine manipulation of the robot deploying the detector is less critical. Current detectors used on robotic systems must either be directly in the vapor plume or make direct contact with the target. By increasing the standoff, detection is more easily and quickly achieved. The end result detector must overcome cross-contamination, sample throughput, and environmental issues. The paper will provide preliminary results of the prototype system to include data, and where feasible, video of testing results.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Russ Ingram and John Sikes "Trace detection of explosives using an in-line high-volume sampler, preconcentrator, and Fido explosives detector", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766415 (29 April 2010); https://doi.org/10.1117/12.850896
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Explosives

Sensors

Particles

Explosives detection

Robotics

Prototyping

Target detection

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