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Deep neural networks are empirically derived systems that have transformed research methods and are driving scientific discovery. Artificial electromagnetic materials, such as electromagnetic metamaterials, photonic crystals, and plasmonics, are research fields where deep neural network results evince the data driven approach; especially in cases where conventional computational and optimization methods have failed. We propose and demonstrate a deep learning method capable of finding accurate solutions to ill-posed inverse problems, where the conditions of existence and uniqueness are violated. A specific example of finding the metasurface geometry which yields a radiant exitance matching the external quantum efficiency of gallium antimonide is demonstrated.

A mid-IR optical emission spectrometer (mid-IR OES) was designed and constructed to detect the absolute spectral radiant exitance of IR signatures. A 256-array PbSe detector was adopted to analyze the mid-IR emission spectrum from countermeasure flares. The spectral response of the optical emission spectrometer was obtained using a directly heated graphite blackbody. The absolute emissions of their IR signatures were inferred by applying spectral response to the spectrum intensity data. Also, we devised a post processing method for compensating diffraction order overlap in a mid- IR grating spectrometer using an array detector. We confirmed the validity of the compensation method by comparing the signal intensities acquired using the different methods.

The absolute spectral radiant exitance of IR signatures from countermeasure flares for mid-IR was experimentally validated by using an optical emission spectrometer. A 256-array PbSe detector was installed to analyze the mid-IR emission spectrum of four IR signatures from countermeasure flares and propellants. We could evaluate the performance of the optical emission spectrometer and verify its usefulness in the field of IR countermeasures. The spectral response of the optical emission spectrometer was calibrated using a directly heated graphite blackbody; in addition, the total uncertainty was analyzed. The absolute amount of emissions of four IR signatures was calculated and compared.

This chapter provides details on calculating signal and noise in thermal imagers. A detectivity model is used to calculate thermal imager contrast threshold function (CTF sys ). CTF sys is used in the targeting task performance (TTP) metric to calculate imager resolution. Thermal imagers sense heat energy with wavelengths between 3 and 12 μm. The 3- to 5-μm band is called midwave infrared (MWIR), and the 8- to 12-μm band is called longwave infrared (LWIR). Figure 9.1 shows typical atmospheric transmission for a 1-km horizontal path. There are three transmission windows from 3 to 4.2 μm, 4.4 to 5 μm, and 8 to 13 μm. Everything near room temperature radiates in the infrared. The emissivity of natural objects is generally above 70%. Most manmade objects are also highly emissive. Thermal sensors derive their images from small variations in temperature and emissivity within the scene. Typically, the thermal scene is very low contrast. Figure 9.2 shows the spectral radiant exitance from blackbodies at 300 K and 303 K. The difference between the two curves is also shown. The difference is small; however, a 3-K contrast represents good thermal imaging conditions.

The measurement of field quantities, that is, flux, flux density, radiance, and intensity, involves the use of a radiometer, an instrument that measures the amount of flux that gets to the detector. Such a measurement requires an appropriate instrument and its calibration. In this chapter we assume that the radiometer can measure the flux with sufficient accuracy. 12.1 Measurement of Power This is the basic measurement. The power on the detector creates a certain electrical signal, and via calibration this represents the power received by the radiometer. Power, normalized to the detector response and spectral band, can be measured by the ESRs described above, by the self-calibrated detectors described above, and by both chopper radiometers and dc radiometers described later. 12.2 Measurement of Incidance Incidance is a flux density. If the radiometer can measure power, it can measure flux density if the area of the entrance aperture is known to sufficient accuracy. Simple division does the job. Of course, it will be the incidance averaged over the area of the entrance aperture. The measurements must be just like the calibration, and the calibration requirements and procedures are described in this chapter. 12.3 Measurement of Exitance Exitance is a source property. It can be inferred from the measurement of power. If the power on the detector is known (by calibration and measurement), then the power from the source can be calculated with certain assumptions. The main assumptions are that the distance and size of the source are known and so is the transmission of the intervening atmosphere. If the atmosphere is not known, many investigators cite an apparent radiant exitance. In this case, apparent means “without correction for atmospheric losses.” This can often be very important. One such case involved understanding the emission from an ICBM. Of course, the rocket had to be measured from a distance, and it radiates copiously in the carbon dioxide band. But the atmosphere absorbs intensely in the carbon dioxide band. The apparent radiant exitance had little relation to the real values.

Landers and rovers are important to solar system exploration, and we are designing and analyzing a remote Raman system for a planetary mission. Raman spectroscopy is a common and powerful technique for materials analysis. We have developed a system that enables Raman spectroscopic measurements at distances of more than 50 meters. In order to design a flight instrument, we need to quantitatively understand the Raman efficiency of natural surfaces. We define remote Raman efficiency as the ratio of radiant exitance leaving a natural surface to the irradiance of the incident laser. The radiant exitance of a natural surface is the product of the sample radiance (minus background), the projected solid angle in steradians, and the spectral bandwidth of the spectrometer. The laser irradiance is the product of the energy of the laser (mJ/pulse) and the pulse rate (Hz), divided by the area of the laser spot. We have determined the remote Raman efficiency for several minerals and rocks: dolomite marble, dacite, milky quartz, anorthosite, calcite, biotite granite, magnesite, chert, gypsum (selenite), fibrous gypsum, and sandstone. By quantifying the remote Raman efficiency, we will be able to determine the number and quality of spectra that a remote Raman system can acquire on a planetary surface where available power is limited. Studies on hematite indicate that Raman shift (and thus remote Raman efficiency) depends on laser wavelength.

The Earth radiation budget experiment (ERBE) was developed to provide a complete temporal and spatial coverage of the solar reflected and Earth emitted radiation. ERB measurements were resumed in 1994 by the Scanner for Radiation Budget (ScaRaB) mission on a single sateffite. Due to sparse temporal sampling, diurnal variations must be accounted for in order to establish accurate unbiased daily and monthly mean radiant exitance. When the ERBE diurnal interpolation algorithm is used alone, large discrepancies are shown between monthly mean radiative flux of single and multi-sateffite measurements. We extend the algorithm by accounting for diurnally varying cloud cover and thickness using ISCCP data. Significant improvements are found in regions where clouds have a pronounced diurnal cycle.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Models of surface temperatures of two land surface types based on their energy budgets were developed to simulate the effects of environmental factors on thermal radiant exitance. The performance of these models is examined in detail. One model solves the non-linear differential equation for heat diffusion in solids using a set of submodels for surface energy budget components. The model performance is examined under three desert conditions thought to be a strong test of the submodels. The accuracy of the temperature predictions and submodels is described. The accuracy of the model is generally good but some discrepancies between some of the submodels and measurements are noted. The sensitivity of the submodels is examined and is seen to be strongly controlled by interaction and feedback among energy components that are a function of surface temperature. The second model simulates vegetation canopies with detailed effects of surface geometry on radiant transfer in the canopy. Foliage solar absorption coefficients are calculated using a radiosity approach for a three layer canopy and long wave fluxes are modeled using a view factor matrix. Sensible and latent heat transfer through the canopy are also simulated using nearby meteorological data but heat storage in the canopy is not included. Simulations for a coniferous forest canopy are presented and the sensitivity of the model to environmental inputs is discussed.

A model is described which determines pyrometer measurements of the temperature of silicon wafers. The wafers may have any combination of silicon polysilicon and 2 on it. The inputs to the model are the wavelength range of the pyrometer temperature film thicknesses and order doping levels and polysilicon grain size. Experimental data provides qualitative agreement to the model. Since the emissivity of the wafer is shown to generally vary with radiation wavelength conventional multi-wavelength pyrometry does not have any obvious ways of compensating for measurement differences due to varying wafer structures. However there may be an empiricalbased alternative for multi-wavelength corrections. 1 Background As rapid thermal processors find their way into commercial applications they are likely to face increasingly tighter requirements in the control of the transient and steady state temperature of the wafer. To achieve this level of control accurate closed loop temperature control is necessary for many commercial applications of rapid thermal processing. The temperature measurement tool usually employed in these closed loop control systems is one or more pyrometers. Pyrometers determine the temperature of the wafer by measuring the magnitude of the radiation being emitted from the wafer. The relationship between temperature and spectral radiant exitance can be expressed as follows: [7] M (1) where M is the spectral radiant exitance of the wafer Mb is the spectral exitance of a black body (both measured in Watts/rn3) and

A room temperature electrical substitution radiometer (ESR) or electrically calibrated null radiometer (ECNR) has been employed to determine the total radiant exitance of a high temperature secondary standard blackbody to illustrate the convenience of a room temperature ESR. Additionally, routine experimental precisions of ±0.13 to 0.05 percent (type A errors) and a derived absolute accuracy of ±0.24 percent (type B errors) for the Stefan-Boltzmann constant determination and ±0.2deg for the blackbody temperature determination have been demonstrated. From the blackbody radiator's temperature, the familiar Stefan-Boltzmann constant is measured within 0.11 percent absolute to the currently accepted value of 5.67051 x 10 12 W-cm -2 -K -4 . Alternatively by applying the accepted Stefan-Boltzmann constant value, the radiator's temperature is derived and shown to be within 0.2 degree at 692.73 K, the zinc freezing point standard and within 0.2 degree at 933.62 K, the aluminum freezing point standard. The uncertainty of the secondary standard blackbody is ±0.2 K following radiometric comparison to zinc and aluminum primary standard blackbodies. By way of introduction, the genesis of 25 determinations of the Stefan-Boltzmann constant, spanning a period of 86 years, is presented to illustrate the evolution of technical advances in analytical methods, the quality of equipment, and refined accuracy.

Meaningful prelaunch calibration of it space sensors requires low-background test facilities for the controlled generation and absolute calibration of radiant flux over wide dynamic ranges. The problems inherent in such measurements are multiplied by the extremely low radiant energy levels at which they have to be performed and by the high selectiveness of most detectors. A procedure is described for the in situ determination of the spectral content of the generated radiant incidance. An analysis of all perti-nent calibration errors is performed. The attainable accuracy is ultimately limited by the inherent uncertainty in our knowledge of the radiant exitance of blackbody-type radiation sources.© (1975) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The Human Resources Laboratory has developed a dynamic IR scene simulation system to support research on simulation requirements for Forward Looking Infrared (FLIR) sensors in fighter aircraft. A primary objective in the development of this system was that FLIR imagery be part of an overall simulation package including navigation and targeting FLIR, Synthetic Aperture Radar (SAR), and out-the-window visual imagery. FLIR imagery is derived from a computer-generated visual scene. To simulate FLIR, color codes for objects in the visual data base are replaced with gray-scale values based on predicted IR exitance. The gray-scale values are constructed using software developed by the Applications Research Corporation which combines feature and surface codes from the Defense Mapping Agency source data together with wavelength dependent absorptivity and run-time scenario specifications including gaming area latitude and longitude, time of day, season, and weather to estimate radiant exitance for each object. Exitance values are then converted into gray-scale values. Sensor effects such as gain level, polarity, field of view, and modulation transfer function are added to the FLIR imagery by a General Electric-developed post-processor. Sensor characteristics can be separately programmed for a navigation FLIR which is presented on a simulated Heads-Up Display (HUD) and for a targeting FLIR. The effects of user inputs to the IR prediction software on radiant exitance, functions of the post-processor, and selection of texture patterns will be discussed. Fidelity requirements for simulation of FLIR in flight training will also be addressed.

A blackbody calibration source designed for operation in a vacuum uses cryogenic coolant and a four-stage controller to provide 0.01 K stability over an operating range from 150 to 350 K, with an absolute uncertainty of less than 0.2 K. The blackbody radiator consists of a black anodized aluminum disk into which is cut concentric grooves that provide a cavity-like enhancement of the blackbody emittance. A gold-plated, temperature-controlled conical reflector with a 5-in. diameter aperture extends the apparent size of the blackbody so that sensors with wide fields of view up to 175 deg conical can be calibrated. A minicomputer-based temperature measurement system converts an embedded array of platinum resistance thermometer (PRT) resistance measurements (traceable to IPTS-68) into blackbody temperature and then calculates the radiant exitance. Data is presented from modeling predictions and actual performance measured during calibration of the ERBE instruments.