As focal plane array technologies advance and imagers increase in resolution, display technology must outpace the
imaging improvements in order to adequately represent the complete data collection. Typical display devices tend to
have an aspect ratio similar to 4:3 or 16:9, however a breed of Wide Field of View (WFOV) imaging devices exist
that skew from the norm with aspect ratios as high as 5:1. This particular quality, when coupled with a high spatial
resolution, presents a unique challenge for display devices. Standard display devices must choose between resizing
the image data to fit the display and displaying the image data in native resolution and truncating potentially
important information. The problem compounds when considering the applications; WFOV high-situationalawareness
imagers are sought for space-limited military vehicles. Tradeoffs between these issues are assessed to the
image quality of the WFOV sensor.
Stand-off detection of potentially hazardous small molecules at distances that allow the user to be safe has many
applications, including explosives and chemical threats. The Naval Surface Warfare Center, Crane Division, with
EYZtek, Inc. of Ohio, developed a prototype stand-off, eye-safe Raman spectrometer. With a stand-off distance greater
than twenty meters and scanning optics, this system has the potential of addressing particularly difficult challenges in
small molecule detection. An overview of the system design and desired application space is presented.
With the ever-increasing dependency on technology in theater, the amount of information that the Warfighter must
monitor and process increases as well. With such a large surge of data, the method of information portrayal is critical.
Gaps exist between the Electro-Optic sensor information and the optimal display to view that information. An
assessment was completed to capture the military display technology gaps by Naval Surface Warfare Center (NSWC)
Crane Division's Electro-Optic Technology Division for many DoD Electro-Optic (EO) systems. The results of these
gaps have been compiled along with predictions of when or if these gaps will be filled based on commercial market
IEDs kill our soldiers and innocent people every day. Lessons learned
from Iraq and Afghanistan clearly indicated that IEDs cannot be detected/defeated by
technology alone; human-technology interaction must be engaged. In most cases, eye
is the best detector, brain is the best computer, and technologies are tools, they must
be used by human being properly then can achieve full functionality. In this paper, a
UV Raman/fluorescence, CCD and LWIR 3 sensor fusion system for standoff IED
detection and a handheld fusion system for close range IED detection are developed
and demonstrated. We must train solders using their eyes or CCD/LWIR cameras to
do wide area search while on the move to find small suspected area first then use the
spectrometer because the laser spot is too small, to scan a one-mile long and 2-meter
wide road needs 185 days although our fusion system can detect the IED in 30m with
1s interrogating time. Even if the small suspected area (e.g., 0.5mx0.5m) is found,
human eyes still cannot detect the IED, soldiers must use or interact with the
technology - laser based spectrometer to scan the area then they are able to detect and
identify the IED in 10 minutes not 185 days. Therefore, the human-technology
interaction approach will be the best solution for IED detection.
An urban-oriented emergency assessment system for airborne Chemical, Biological, and Radiological (CBR) threats, called CT-Analyst and based on new principles, gives greater accuracy and much greater speed than possible with current alternatives. This paper explains how this has been done. The increased accuracy derives from detailed, three-dimensional CFD computations including, solar heating, buoyancy, complete building geometry specification, trees, wind fluctuations, and particle and droplet distributions (as appropriate). This paper shows how a very finite number of such computations for a given area can be extended to all wind directions and speeds, and all likely sources and source locations using a new data structure called Dispersion Nomographs. Finally, we demonstrate a portable, entirely graphical software tool called CT-Analyst that embodies this entirely new, high-resolution technology and runs effectively on small personal computers. Real-time users don't have to wait for results because accurate answers are available with near zero-latency (that is 10 - 20 scenarios per second). Entire sequences of cases (e.g. a continuously changing source location or wind direction) can be computed and displayed as continuous-action movies. Since the underlying database has been precomputed, the door is wide open for important new real-time, zero-latency functions such as sensor data fusion, backtracking to an unknown source location, and even evacuation route planning. Extensions of the technology to sensor location optimization, buildings, tunnels, and integration with other advanced technologies, e.g. micrometeorology or detailed wind field measurements, will be discussed briefly here.
While ion mobility spectrometry (IMS) has been used as a portable trace vapor detector, these handheld systems suffer from poor selectivity. Their low resolution makes confident identification of chemical species difficult. One major application for these IMS systems is in Homeland Defense. IMS systems are fielded for the detection of chemical warfare agents, explosives, narcotics, and other hazardous chemicals. Recently, a novel signal processing methodology using wavelet filtering, statistical evaluators, and genetic algorithms was demonstrated to improve sensitivity and specificity of an ion mobility spectrometer. Previous work involved a single (single polarity) IMS cell. Since both positive and negative ions are created in the same environment and a common sample interface is used for the dual IMS system, there is cross talk between the positive and negative cell. Typically, this cross talk provides little information on the identity of the chemical species present. However, using this new methodology, valuable sample information is obtained. Moreover, ion beam modulation has been incorporated to allow for the ion beam to be broken up into discrete packets. The modulation allows the rejection of common background interferents. This paper will present the process of using cell cross talk, ion beam modulation, and application and extension of the signal processing methodology. The application to field instrumentation will also be discussed.
Novel methodology has been developed that simultaneously improves sensitivity and specificity of a low-resolution ion mobility spectroscopy (IMS) sensor. Wavelet transforms have been applied to IMS spectra in order to de-noise and enhance spectral features. Next, trigger metrics of the spectra were derived using a statistical evaluator (SE) and optimized using a genetic algorithm (GA). The combination of wavelets, SE, and GA has been demonstrated to differentiate between background, analyte, interferent, and a binary mixture of analyte and interferent. This results in an overall increase in resolving power. The new system is less sensitive to false positives due to increased selectivity, shows the ability to yield quantitative data at ultra-low concentrations for low level toxicity, has the ability to detect binary mixtures of compounds, and shows great potential in significantly improving chemical warfare detection capabilities under field conditions.