Signature Simulation and Characterization of Mixed Solids in the Visible and Thermal Regimes

Solid target signatures vary due to geometry, chemical composition and scene radiometry. Although radiative transfer models and function-fit physical models may describe certain targets in limited depth, the ability to incorporate all three of these signature variables is difficult. This work describes a method to simulate the transient signatures of mixed solids and soils by first considering scene geometry that was synthetically created using 3-d physics engines. Through the assignment of spectral data from the Nonconventional Exploitation Factors Data System (NEFDS) and other libraries, synthetic scenes are represented as a chemical mixture of particles. Finally, first principles radiometry is modeled using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. With DIRSIG, radiometric and sensing conditions were systematically manipulated to produce goniometric signatures. The implementation of this virtual goniometer allows users to examine how a target bidirectional reflectance function (BRDF) and directional emissivity will change with geometry, composition and illumination direction. The tool described provides geometry flexibility that is unmatched by radiative transfer models. It delivers a discrete method to avoid the significant cost of time and treasure associated with hardware based goniometric data collections

Empirical Measurement and Model Validation of Infrared Spectra of Contaminated Surfaces

The goal of this thesis was to validate predicted infrared spectra of liquid contaminated surfaces from a micro-scale bi-directional reflectance distribution function (BRDF) model through the use of empirical measurement. Liquid contaminated surfaces generally require more sophisticated radiometric modeling to numerically describe surface properties. The Digital Image and Remote Sensing Image Generation (DIRSIG) model utilizes radiative transfer modeling to generate synthetic imagery for a variety of applications. Aside from DIRSIG, a micro-scale model known as microDIRSIG has been developed as a rigorous ray tracing physics-based model that could predict the BRDF of geometric surfaces that are defined as micron to millimeter resolution facets. The model offers an extension from the conventional BRDF models by allowing contaminants to be added as geometric objects to a micro-facet surface. This model was validated through the use of Fourier transform infrared spectrometer measurements. A total of 18 different substrate and contaminant combinations were measured and compared against modeled outputs. The substrates used in this experiment were wood and aluminum that contained three different paint finishes. The paint finishes included no paint, Krylon ultra-flat black, and Krylon glossy black. A silicon based oil (SF96) was measured out and applied to each surface to create three different contamination cases for each surface. Radiance in the longwave infrared region of the electromagnetic spectrum was measured by a Design and Prototypes (D\&P) Fourier transform infrared spectrometer and a Physical Sciences Inc. Adaptive Infrared Imaging Spectroradiometer (AIRIS). The model outputs were compared against the measurements quantitatively in both the emissivity and radiance domains. A temperature emissivity separation (TES) algorithm had to be applied to the measured radiance spectra for comparison with the microDIRSIG predicted emissivity spectra. The model predicted emissivity spectra was also forward modeled through a DIRSIG simulation for comparisons to the radiance measurements. The results showed a promising agreement for homogeneous surfaces with liquid contamination that could be well characterized geometrically. Limitations arose in substrates that were modeled as homogeneous surfaces, but had spatially varying artifacts due to uncertainties with contaminant and surface interactions. There is high desire for accurate physics based modeling of liquid contaminated surfaces and this validation framework may be extended to include a wider array of samples for more realistic natural surfaces that are often found in real world scenarios

A Study of Bi-Directional Reflectance Distribution Functions and Their Effects on Infrared Signature Models

Since 2004, AFIT has been developing a trend-analysis tool to assess large commercial aircraft infrared (LCAIR) signatures. In many cases, this code predicted signatures to within 10% of measured data. However, other results indicated that the single-bounce, specular-reflection algorithm being used failed to adequately simulate interactions between aircraft parts where either the specular component is dominated by diffuse reflection or part-to-part multiple-bounce reflections contribute significantly to the signature. This research incorporates Bi-Directional Reflectance Distribution Functions (BRDF\u27s) and multiple-bounce calculations into the LCAIR model. A physical aircraft model was constructed from aluminum, and measurements were taken before and after a surface treatment in gloss black paint. The Sandford-Robertson model is used to parameterize the BRDF\u27s of both the bare aluminum and gloss black paint. Since the most efficient method of integrating a BRDF depends upon the reflectance distribution of the aircraft material, the sampling resolution of the BRDF integral is crucial to an accurate simulation. Additionally, care is taken to ensure that the integration of the hemispherical irradiance onto each facet of the computational model is sampled at a sufficient resolution to achieve convergence in the solution. Simulations in the mid-wave infrared (MWIR) and long-wave infrared (LWIR) bands validate both the previous specular reflectance simplification for the gloss black simulations and the failure of the previous algorithm for the highly reflective bare aluminum. The necessity of considering multiple bounces in the simulation is also demonstrated amongst part-to-part reflections near the wing root, where three or four bounces are required for the solution to converge. Finally, three scenarios simulating a man-portable air defense system (MAN-PADS) system engaging an Airbus A340-300 aircraft landing at a generic airport are performed

Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery

Determination of the internal temperature of a mechanical draft cooling tower (MDCT) from remotely-sensed thermal imagery is important for many applications that provide input to energy-related process models. The problem of determining the temperature of an MDCT is unique due to the geometry of the tower and due to the exhausted water vapor plume. The radiance leaving the tower is dependent on the optical and thermal properties of the tower materials (i.e., emissivity, BRDF, temperature, etc.) as well as the internal geometry of the tower. The tower radiance is then propagated through the exhaust plume and through the atmosphere to arrive at the sensor. The expelled effluent from the tower consists of a warm plume with a higher water vapor concentration than the ambient atmosphere. Given that a thermal image has been atmospherically compensated, the remaining sources of error in extracted tower temperature due to the exhausted plume and the tower geometry must be accounted for. A temperature correction factor due to these error sources is derived through the use of three-dimensional radiometric modeling. A range of values for each important parameter are modeled to create a target space (i.e., look-up table) that predicts the internal MDCT temperature for every combination of parameter values. The look-up table provides data for the creation of a fast-running parameterized model. This model, along with user knowledge of the scene, provides a means to convert the image-derived apparent temperature into the estimated absolute temperature of an MDCT

Polarimetric modeling of remotely sensed scenes in the thermal infrared

This dissertation develops a polarimetric thermal infrared (IR) framework within the Digital Image and Remote Sensing Image Generation (DIRSIG) software tool enabling users in the remote sensing community to conduct system level trades and phenomenology studies. To support polarized reflection and emission modeling within DIRSIG, a generalized bi-directional reflectance distribution function (BRDF) is presented. This generalized form is a 4x4 element Mueller matrix that may be configured to resemble the commonly utilized Beard-Maxwell or Priest-Germer BRDF models. A polarized emissivity model is derived that leverages a hemispherical integration of the polarized BRDF and Kirchoff\u27s Law. A portable experimental technique for measuring polarized long-wave IR emissivity is described. Experimental results for sixteen target and background materials are fit to the polarized emissivity model. The resulting model fit parameters are ingested by DIRSIG to simulate polarized long-wave infrared scene phenomenology. Thermally emitted radiance typically has a vertical polarization orientation, while reflected background radiance is polarized horizontally. The balance between these components dictates what polarized signature (if any) is detected for a given target. In general, specular targets have a stronger emission polarization signature compared to diffusely scattering targets consistent with visible polarimetry findings. However, the influence of reflected background radiance can reduce the polarimetric signature of specular targets below a detectable threshold. In these situations, a diffusely scattering target may actually exhibit a polarization signature stronger than a specular target material. This interesting phenomenology is confirmed by experimental scene collections and DIRSIG simulations. Understanding polarimetric IR phenomenology with this level of detail is not only key for system design, but also for determining optimal collection geometries for specific tactical missions

Daytime Detection of Space Objects

Space Situational Awareness (SSA) requires repeated object updates for orbit accuracy. Detection of unknown objects is critical. A daytime model was developed that evaluated sun flares and assessed thermal emissions from space objects. Iridium satellites generate predictable sun glints. These were used as a model baseline for daytime detections. Flares and space object thermal emissions were examined for daytime detection. A variety of geometric, material and atmospheric characteristics affected this daytime detection capability. In a photon noise limited mode, simulated Iridium flares were detected. The peak Signal-to- Noise Ratios (SNR) were 6.05e18, 9.63e5, and 1.65e7 for the nighttime, daytime and infrared flares respectively. The thermal emission of space objects at 353K, 900K and 1300K with 2 to 20 m2 emitting areas were evaluated. The peak emission was for the 20 m2 900K object with an SNR of 1.08e10. A number of barriers remain to be overcome if daytime detection of space objects can be achieved. While the above SNR values are large, this is based on optimal detection. The SBR\u27s were less than 1 for all cases. Image post-processing will be necessary to extract the object from the background. Successful daytime detection techniques will increase sensor utilization times and improve SSA

Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination

Bidirectional reflectance measurement of tungsten samples to assess reflection model in WEST tokamak

This paper presents the measurement of the bidirectional reflectance distribution function of tungsten (W) samples and the resulting reflection models in the nuclear fusion device WEST (tokamak). For this, an experimental gonio-spectrophotometer was developed to fully characterize the material’s optical and thermal-radiative properties of metallic samples with different roughnesses. Ray-tracing photonic simulation was then carried out to predict the photon behavior in a fully metallic environment as a function of reflectance measurement. Low emissivity (0.1 at 4 μm) and highly specular reflectance (fitting with a Gaussian distribution around the specular direction with a small width lower than 10°) are found for W samples. These measurements have been used as input for the photonic simulation, and the resulting synthetic image reproduced the reflection features well on the upper divertor, detected in WEST infrared experimental images

Land Surface Temperature Measurements form EOS MODIS Data

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered

Directional Thermal Emission and Absorption from Surface Microstructures in Metalized Plastics

Thermal emission, exhibiting antenna-like directivity, has been generated by a wide variety of both simple and complex micro-structures. The basic demonstrations of directional emission, and specific device performance evaluations, have been conducted at elevated temperatures, typically several hundred degrees Celsius. The most common applications for these high-temperature designs are thermal photo-voltaic and spectroscopic sources. A wide range of lower temperature applications, such as spacecraft thermal management and mid- to far-infrared optical train stray light management, are precluded by the cost and complexity of the fabrication processes employed. In this work, a novel fabrication and physical surface optimization of a seminal directionally emitting structure is conducted in metalized plastic. The fabrication method is derived from the high-throughput compact disc manufacturing process and exploits the advantageous surface electromagnetic properties of aluminium, at the expense of forgoing high-temperature operation. Then, a novel directionally emitting structure, exhibiting a broader angular response, is design and fabricated by the same methods. The performance of both structures is evaluated through reflectance and self-emission measurements, and compared to rigorous modeling results. The necessity of conducting low-temperature emission and reflectance measurements, on instruments designed for radiometry rather than scatterometry, requires consideration of the longitudinal spatial coherence of field incidence on the surface. To this end, a well-developed modeling method was extended to include finite longitudinal spatial coherence excitation