Mr. William J. Underwood Profile

William J. Underwood

at US Army RDECOM

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Publications (4)

Proceedings Article | 29 December 2004 Paper

Micro-UV detector

Jerry Cabalo, Richard Sickenberger, William Underwood, David Sickenberger

Proceedings Volume 5617, (2004) https://doi.org/10.1117/12.569260

KEYWORDS: Particles, Sensors, Luminescence, Atmospheric particles, Ultraviolet radiation, Aerosols, Mirrors, UV optics, Visualization, Signal to noise ratio

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Proceedings Article | 1 September 2004 Paper

Micro UV detector

Jerry Cabalo, Richard Sickenberger, William Underwood, David Sickenberger

Proceedings Volume 5417, (2004) https://doi.org/10.1117/12.539980

KEYWORDS: Particles, Sensors, Ultraviolet radiation, Luminescence, Atmospheric particles, Mirrors, Aerosols, Light emitting diodes, Optical resonators, Visible radiation

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Proceedings Article | 1 April 2003 Paper

CB detection and early warning--fusing disparate sensors into the detection process: program overview

Amnon Birenzvige, David Sickenberger, Felix Reyes, William Underwood, Christian Reiff, David Gonski, Monique Fargues, Bruce Nelson

Proceedings Volume 5099, (2003) https://doi.org/10.1117/12.497980

KEYWORDS: Sensors, Artillery, Situational awareness sensors, Acoustics, Biological detection systems, Information fusion, Detection and tracking algorithms, Roads, Cameras, Computer intrusion detection

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Improved situational awareness is a primary goal for the Objective Force. Knowing where the enemy is and what are the threats to his troops provides the commander with the information he needs to plan his mission and provide his forces with maximum protection from the variety of threats that are present on the battlefield. Sensors play an important role in providing critical information to enhance situational awareness. The sensors that are used on the battlefield include, among others, seismic, acoustic, and cameras in different spectral ranges of the electro-magnetic spectrum. These sensors help track enemy movement and serve as part of an intrusion detection system. Characteristically these sensors are relatively cheap and easy to deploy. Chemical and biological agent detection is currently relegated to sensors that are specifically designed to detect these agents. Many of these sensors are collocated with the troops. By the time alarm is sounded the troops have already been exposed to the agent. In addition, battlefield contaminants frequently interfere with the performance of these sensors and result in false alarms. Since operating in a contaminated environment requires the troops to don protective garments that interfere with their performance we need to reduce false alarms to an absolute minimum. The Edgewood Chemical and Biological Center (ECBC) is currently conducting a study to examine the possibility of detecting chemical and biological weapons as soon as they are deployed. For that purpose we conducted a field test in which the acoustic, seismic and electro-magnetic signatures of conventional and simulated chemical / biological artillery 155mm artillery shells were recorded by an array of corresponding sensors. Initial examination of the data shows a distinct differences in the signatures of these weapons. In this paper we will provide detailed description of the test procedures. We will describe the various sensors used and describe the differences in the signatures generated by the conventional and the (simulated) chemical rounds. This paper will be followed by other papers that will provide more details information gained by the various sensors and describe how fusing the data enhance the reliability of the CB detection process.

Proceedings Article | 1 April 2003 Paper

CB round discrimination fusing visible and infrared camera data

Bruce Nelson, Amnon Birenzvige, William Underwood, David Sickenberger

Proceedings Volume 5099, (2003) https://doi.org/10.1117/12.499294

KEYWORDS: Cameras, Visible radiation, Imaging systems, Infrared cameras, Optical sensors, Long wavelength infrared, Video, Feature extraction, Explosives, Lithium

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In support of the Disparate Sensor Integration (DSI) Program a number of imaging sensors were fielded to determine the feasibility of using information from these systems to discriminate between chemical simulant and high explosives munitions. The imaging systems recorded video from 160 training and 100 blind munitions detonation events. Two types of munitions were used; 155 mm high explosives rounds and 155 mm chemical simulant rounds. In addition two different modes of detonation were used with these two classes of munitions; detonation on impact (point detonation) and detonation prior to impact (airblasts). The imaging sensors fielded included two visible wavelength cameras, a near infrared camera, a mid wavelength infrared camera system and a long wavelength infrared camera system. Our work to date has concentrated on using the data from one of the visible wavelength camera systems and the long wavelength infrared camera system. The results provided in this paper clearly show the potential for discriminating between the two types of munitions and the two detonation modes using these camera data. It is expected that improved classification robustness will be achieved when the camera data described in this paper is combined with results and discriminating features generated from some of the other camera systems as well as the acoustic and seismic sensors also fielded in support of the DSI Program. The paper will provide a brief description of the camera systems and provide still imagery that show the four classes of explosives events at the same point in the munitions detonation sequence in both the visible and long wavelength infrared camera data. Next the methods used to identify frames of interest from the overall video sequence will be described in detail. This will be followed by descriptions of the features that are extracted from the frames of interest. A description of the system that is currently used for performing classification with the extracted features and the results attained on the blind test data set are next described. The work performed to date to fuse information from the visible and long wavelength infrared imaging sensors including the benefits realized are next described. The paper concludes with a description of our ongoing work to fuse imaging sensor data.

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