Contrast signal to noise ratio (CSNR) is an important metric for a thermal camera. Listing two, it guides a system architect to design the camera for a desired performance. It predicts the performance of the camera for a given scenario. Many an author developed its formulas and used them. Holst presented them systematically in his textbook. The formulas for CSNR are not always the same one another for they are derived under different assumptions and approximations. This paper reviews some and presents improved formulas for both the point source and the extended source. They are compared to others in the literature, delineating the improvement. The formulas are applied to one scenario as an example.
Non-uniformity correction (NUC) is a standard procedure for infrared (IR) cameras. The effect of lens temperature, however, is often ignored during the implementation of a NUC. Ignoring the effect of temperature is acceptable if the lens temperature is at much lower than ambient temperature, whose irradiance onto the focal plane array (FPA) is much less than that of the scene. Ignoring the effect of temperature is also acceptable if the lens temperature during the calibration for NUC is the same as that during the scene collection. The change of the lens temperature in between the calibration for NUC and the scene collection, however, affects the performance. Such degradation in image quality is presented by the frames taken by a mid-wave infrared (MWIR) camera. An empirical law is established to mitigate the effect of lens temperature, which offers various options for NUC. As an example, we propose a four-point NUC that mitigates the effect of the lens temperature. We demonstrate its usefulness by applying it to the frames taken at various lens temperatures. The results are satisfactory.
In modeling and characterizing a focal plane array (FPA) with a uniform source, estimating the irradiance on the FPA is
inevitable. Many have developed needed formulas for the estimate. Those formulas mostly focus on one pixel of the
FPA on the optical axis, ignoring all the other pixels. I use Foote’s law here to derive the formulas for all the pixels in a
simple configuration where the FPA is directly exposed to the uniform source. I extend the formulas for two more
configurations: the FPA enclosed with a baffle and the FPA housed with a lens. My results are compared with some
existing formulas. They show differences, yet reach an agreement with some approximations. My formulas are useful for
modeling and trade study for cameras, especially for the cameras with wide field of view.
Infrared (IR) cameras are widely used in systems to search and track. IR search and track (IRST) systems are most often available in one of two distinct spectral bands: mid-wave IR (MWIR) or long-wave IR (LWIR). Many have compared both systems in a number of ways. The comparison included field data and analysis under different scenarios. Yet, it is a challenge to make a right decision in choosing one band over the other band for a new scenario. In some respects, the attempt is like choosing between an apple and an orange. The signal-to-noise ratio (SNR) of a system for a point-like target is one criterion that helps one to make an informed decision. The formula for SNR commonly uses noise equivalent irradiance (NEI) that requires front optics. Such formalism cannot compare two bands before a camera is built complete with front optics. We derive a formula for SNR that utilizes noise equivalent differential temperature (NEDT) that does not require front optics. The formula is further simplified under some assumptions, which identifies critical parameters and provides an insight in comparing two bands. We have shown an example for a simple case.
Most of imaging polarimeters in the field measure only a few components of the Mueller matrix or their combinations
such as Stokes vector, degree of linear polarization (DOLP) and degree of circular polarization (DOCP). Our imaging
polarimeter was similar in that it produced two combinations of 16 Mueller components. We upgraded our polarimeter
to acquire the Mueller matrix of a scene in the field (Mueller image). Scenes consisted of flat plates mounted on a large
panel, a large cylinder, and natural background such as trees and grass. We established a formula to derive Mueller
images from the measurements with our instrument. Mueller images provided comprehensive information about the
polarization effect on any targets in the scene, which were useful in distinguishing man-made objects from natural
background. In addition, Mueller images enabled us to emulate some images by imaging polarimeters with limited
capability. Comparison of those images with Mueller images provided an insight on the effectiveness and shortcomings
of the associated imaging polarimeters.
We carried out ghost imaging experiments using nondegenerate entangled beams with the central wavelengths at 810 nm
and 1550 nm. The pulsed pump at 532 nm had the high efficiency of parametric down conversion and enabled ghost
imaging although its average pump power was 10 mW. For the first time, we demonstrated ghost imaging with two
disparate detectors: Si avalanche photodiode on one arm and InGaAs avalanche photodiode on the other. Objects were
placed in the arm of the 1550 nm beam, whereas the imaging lens was placed in the arm of the 810 nm beam. Ghost
imaging was constructed by using the quantum correlated portion of the data due to the nature of the entangled beams.
Current theory for this configuration predicted that the image magnification by a degenerate source should be one and
half times larger than that of this nondegenerate source; the observed magnification followed closely the value predicted
by the theory.
We observed the second order correlation peak for nondegenerate spontaneous parametric down conversion (SPDC) of a
pulsed pump at 532 nm into 810 nm and 1550 nm entangled beams. We used a Si avalanche photodiode (APD) to detect
the 810 nm photons, and an InGaAs APD to detect those at 1550 nm. We defined both a visibility and signal-to-noise
ratio (SNR) based on the data, which were obtained at various pump powers. In contrast to classical imaging systems,
for which SNR increases monotonically with transmitted power, the SNR for the correlation peak in our setup exhibited
a gradual decay as the pump power increased. We derived an empirical relation for the SNR, which was inversely
proportional to the square root of pump power.
Our objective is to disseminate the importance of sensing geometry when comparing reflectance data from different polarimeters. Results are presented from an eye-safe laser scatterometer that was used to measure the Mueller matrix of samples under a diversity of sensing geometries, thus providing a common reference for instrument comparison. Data from three other polarimeters are compared to this reference, and apparent discrepancies are explained in terms of each instrument's unique experimental sensing geometry. Results are also provided showing that the degree of sensing geometry dependence varied widely among sample types.
Quantum imagers have been demonstrated in the laboratory by several groups. However, there are many practical
concerns that must be considered in order to make such a system as successful as classical imagers in field applications.
Consequently, we develop a model for signal-to-noise ratio (SNR) to estimate the performance of a quantum imager in
comparison with that of the classical case. We assume simple architectures for both systems with components in the two
as common to each other as possible. Comparisons between the imagers are made under conditions of solar background
for ranges up to 2 km. The performance of quantum imager is shown to be superior to that of the classical case under
conditions of narrow joint (or coincidence) detection windows and very strong pumping of the spontaneous parametric
downconverter illumination source, for which the degree of photon entanglement may be severely degraded.
The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research
Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users
within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution,
physics-based Infrared (IR) target and background signature model for tactical weapon applications and has
grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame
imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model
(1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and
software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was
released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the
reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the
unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the
validation test results of the Irma passive models and discuss the new features in Irma 5.2.
We report on a set of measurements made in December 2005 by researchers from the University of Central Florida, SPAWAR's Innovative Science and Technology Experiment Facility (ISTEF), Harris Corporation, NASA Kennedy Space Center, and Northrop Grumman. The experiments were conducted on the Shuttle Landing Facility (SLF) at Kennedy Space Center (KSC) over terrestrial paths of 1, 2, and 5 km. The purpose of the experiments was to determine the atmospheric-induced beam spreading and beam wander at various ranges. Two lasers were used in the experiments. Both were a pulsed 1.06 μm laser; however, one was single-mode and the other was multi-mode. Beam profiles were recorded near the target position. Simultaneous measurements of Cn2, wind speed and direction, humidity, visibility, temperature, and surface temperature profiles were all recorded.
The Irma synthetic signature prediction code is being developed to facilitate the research and development of multi-sensor systems. Irma was one of the first high resolution, physics-based Infrared (IR) target and background signature models to be developed for tactical weapon applications. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel, and a Doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Irma is currently used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. In 2005, Irma version 5.1 was released to the community. In addition to upgrading the Ladar channel code to an object oriented language (C++) and providing a new graphical user interface to construct scenes, this new release significantly improves the modeling of the ladar channel and includes polarization effects, time jittering, speckle effect, and atmospheric turbulence. More importantly, the Munitions Directorate has funded three field tests to verify and validate the re-engineered ladar channel. Each of the field tests was comprehensive and included one month of sensor characterization and a week of data collection. After each field test, the analysis included comparisons of Irma predicted signatures with measured signatures, and if necessary, refining the model to produce realistic imagery. This paper will focus on two areas of the Irma 5.1 development effort: report on the analysis results of the validation and verification of the Irma 5.1 ladar channel, and the software development plan and validation efforts of the Irma passive channel. As scheduled, the Irma passive code is being re-engineered using object oriented language (C++), and field data collection is being conducted to validate the re-engineered passive code. This software upgrade will remove many constraints and limitations of the legacy code including limits on image size and facet counts. The field test to validate the passive channel is expected to be complete in the second quarter of 2006.
The Irma synthetic signature prediction code is being developed to facilitate the research and development of multisensor systems. Irma was one of the first high resolution Infrared (IR) target and background signature models to be developed for tactical weapon application. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel and the doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Since 2000, additional capabilities and enhancements have been added to the ladar channel including polarization and speckle effect. Work is still ongoing to add time-jittering model to the ladar channel. A new user interface has been introduced to aid users in the mechanism of scene generation and running the Irma code. The user interface provides a canvas where a user can add and remove objects using mouse clicks to construct a scene. The scene can then be visualized to find the desired sensor position. The synthetic ladar signatures have been validated twice and underwent a third validation test near the end of 04. These capabilities will be integrated into the next release, Irma 5.1, scheduled for completion in the summer of FY05. Irma is currently being used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. The purpose of this paper is to report the progress of the Irma 5.1 development effort.