In an experimental setting where new sensing techniques are being developed and the source/medium/system parameters
are in a constant state of change, a flexible radiometric prediction tool can be essential for experimental design and
analysis. The Spectral Signature Sensing (SSS) analysis and visualization software development is a user-friendly
analytic tool that is designed for radiometric analysis and modeling of radiant optical energy from a source to a detection
system. Transmission through the atmosphere is computed with MODTRAN and the code features multiple-source
options and a flexible set of parameters for the detector. It also provides a Google Earth display function to visualize the
simulation scenario. In this paper a summary is presented of the radiometric calculations applied in this modeling tool.
The essential components and the main features are briefly described including the system-component inputs, other
options such as save and load inputs, and the resulting spectral plots and radiometric output.
Sensor technologies are undergoing revolutionary advances, as seen in the rapid growth of multispectral methodologies. Increases in spatial, spectral, and temporal resolution, and in breadth of spectral coverage, render feasible sensors that function with unprecedented performance. A system was developed that addresses many of the key hardware requirements for a practical dual-band multispectral acquisition system, including wide field of view and spectral/temporal shift between dual bands. The system was designed using a novel dichroic beam splitter and dual band-pass filter configuration that creates two side-by-side images of a scene on a single sensor. A high-speed CMOS sensor was used to simultaneously capture data from the entire scene in both spectral bands using a short focal-length lens that provided a wide field-of-view. The beam-splitter components were arranged such that the two images were maintained in optical alignment and real-time intra-band processing could be carried out using only simple arithmetic on the image halves. An experiment related to limitations of the system to address multispectral detection requirements was performed. This characterized the system’s low spectral variation across its wide field of view. This paper provides lessons learned on the general limitation of key hardware components required for multispectral muzzle flash detection, using the system as a hardware example combined with simulated multispectral muzzle flash and background signatures.
KEYWORDS: Near infrared, Sensors, Potassium, Alkali metals, Doppler effect, Signal to noise ratio, Imaging systems, Silicon, Signal attenuation, Absorption
Utilization of Near-Infrared (NIR) spectral features in a muzzle flash will allow for small arms detection using low cost
silicon (Si)-based imagers. Detection of a small arms muzzle flash in a particular wavelength region is dependent on the
intensity of that emission, the efficiency of source emission transmission through the atmosphere, and the relative
intensity of the background scene. The NIR muzzle flash signature exists in the relatively large Si spectral response
wavelength region of 300 nm-1100 nm, which allows for use of commercial-off-the-shelf (COTS) Si-based detectors.
The alkali metal origin of the NIR spectral features in the 7.62 × 39-mm round muzzle flash is discussed, and the basis
for the spectral bandwidth is examined, using a calculated Voigt profile. This report will introduce a model of the 7.62 ×
39-mm NIR muzzle flash signature based on predicted source characteristics. Atmospheric limitations based on NIR
spectral regions are investigated in relation to the NIR muzzle flash signature. A simple signal-to-clutter ratio (SCR)
metric is used to predict sensor performance based on a model of radiance for the source and solar background and pixel
registered image subtraction.
Methods are examined for modeling ultra narrow band signature propagation through both natural and optically dense or obscured atmospheres. The impetus for the study comes from the recent exploitation of (ultra)narrow band atomic line filters which have become practical for remote sensing applications and real battlefield sensors. Aside from the obvious advantage of being able to "squeeze" the narrow-band signal through (near) equally narrow-band "windows" of the natural (gaseous) atmoshpere; there are a number of other issues that come into play that are either negligible or irrelevant in the more usual broadband applications but may be important here. For example, another way the technology can be exploited is by selecting the filter wavelength so as to take advantage of the Fraunhofer absorption lines in the solar spectrum, thsu producing an effective "solar blind" sensor and the attendant advantages thereof. In this paper we address both practical issues such as line broadening by various known atmosphere processes, including extinction and scattering by suspended aerosols and adverse weather, as well as some more subtle issues such as the effect of the wavelength shift due to atmospheric refraction and Doppler shifting due to the relative motion of the Earth with respect to the Sun; both of which though admitted small and thus negligible in broadband applications could be important here. Our main technical approach is through simulation using conventional models such as MODTRAN and EOSAEL (battlefield atmospheres), augmented as necessary for the task at hand. Preliminary results based on side-by-side comparisons with conventional broadband technologies (e.g., interference filters, Δλ≈10nm, FWHM) are discussed and shows both advantages and disadvantages of the narrow-band technology.
Methods are examined for modeling signature propagation through optically dense atmospheres accounting for both direct signal attenuation, isotropic scattering, and strong forward (multiple) scattering considering both existing analytical approaches and numerical Monte Carlo photon transport simulations. Examples are given for the case of upward propagation through plane layers in the form of angular distribution functions, based on a point source of light, from which one can determine an atmospheric modulation transfer function (MTF) widely used in simulating the effects of obscurants in imaging systems performance models. Methods can also be used to estimate correction factors for compensating errors in transmission measurements due to multiple forward scattering into the sensor field of view. Results suggest that even at large optical thicknesses where the directly transmitted signal is minimal, there is enough spatial contrast in the diffuse signal to make point sources detectable. However the major effect is on the broadening of the received signal which for the case of isotropic scattering yielded values on the order of 5-10 m for the width of the point spread function (PSF) for a sensor field of view of 100 milliradians. For more intense forward scattering the relative signal strength is increased and the PSF widths are decreased.
The use of Surface Enhanced Raman Scattering (SERS) for biological detection has brought up the question of detection limits and how these detection limits apply to the application. For most biological detection uses of SERS, a high detection probability is needed for a relatively small amount of biological specimen. This is especially true for the detection of S. enteriditis (Salmonella) bacteria that may be present on minute concentrations , for example, in food products. Using SERS we have identified the associated antibody conjugated with 12nm diameter Au colloid. Our preliminary results show small fractals with a disperse distance of about 1 monomer diameter (12nm) between the colloidal gold monomers may enhance the SERS emission. We also investigate the possibility that a conformation change may induce an increase in the aromatic amino acid contribution. We then compare the antibody SERS alone to SERS of antibody conjugated to Salmonella bacteria. The use of SERS as a bacterial detection method leads to the possibility for detection of small amounts (<10,000 bacteria/ml) of Salmonella bacteria. In our study we obtained a detection limit of 106 bacteria/ml using gold as a SERS active substrate.
We examine the relationship between atmospheric-induced clutter, driven mainly by temporal variations of obscuring aerosols, and the more usual clutter attributed to spatial variations in natural background scenes. Our main approach is through the analysis of time dependent transmission-radiance measurements obtained during field experiments and through existing theories exploited in atmospheric models for generating effects of natural weather types and man made (battlefield) obscurants. We couple the obscurant modeling with other existing models for simulating natural background scenes and examine the effects of the obscurants on various scenes using recently developed analytical methods for calculating clutter metrics. Our selected clutter metric is based on what we call the block filter method that quantifies IR clutter in terms of potential false targets based on scene statistics. Our main focus is on the effects of direct transmittance, path radiance, and turbulence driven noise at multiple wavelength regimes. Preliminary results from field data show strong cross-band correlations in measured path transmission obtained over collinear lines of sight and wavelengths from the visible to infrared. The same trend holds for measured path radiance, most rigorously at the shorter wavelengths (visible and near infrared), but with a significantly enhanced noise component at the infrared wavelengths (mid and far infrared) where the effect of obscurant thermal emission comes into play. From the analysis of the imagery we have also detected both emissive and reflective contributions to the path radiance. We apply the results to four background scenes of varying degree of complexity and report the results in terms of a clutter metric representative of the particular background under both clear air and obscured conditions.
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