Unlassfied(Continuedl) tot~~T rams~tAT~ OF Tgo"" 4WS (t "V 4sJAisUca ẽ J"2A Unclassified SECURITY CLASSIPICATION OP THIS PAGE(tmý Oat. bw. 20. ABSTRACT (Continued). signature significantly different from its surround. The thrust in the United States to further develop IR target acquisition and surveillance capabilities and the thrust in the North Atlantic Treaty Organization (NATO) community to camouflage or conceal critical elements at fixed installations from such devices have focused attention on the need to better understand the character of the thermal Ii signatures of not only targets but also their surrounds. To date, considerably more effort has been focused on targets than or surrounds. The Terrain Surface Temperature Model (TSTM) presented herein, was developed to help fill the void in the understanding of thermal IR signatures. of natural terrain surfaces and of some cultural features. The model estimates temperatures of actual or hypothetical material systems and for actual or hypothetical weather conditions. The model handles sensible heat transfer, latent heat transfer, the impact of cloud type and cover, and seasonal/ geothermal heat fluxes. The material system can be handled as a multilayered medium with discrete physical and thermal properties assigned to each layer. This report documents the TSTh by presenting a discussion of the mathematics of the model, a discussion of the computer program input file and its operation, and the results of a sensitivity analyses and limited verification tests conducted with the model. Typical parameter values of material systems descriptors used in the model are included in an appendix. ?i _ eatu,,iv C•.*saCAtou OP, lies ,*ugatw sa ahm PREFACE The study reported herein was conducted by personnel of the U. S.
The goal of the Countermine Computational Testbed Sensor Model Development Program is to design a software simulation for candidate airborne imaging sensors suitable for use in the remote detection of mines. The simulation takes as input several sensor parameters and a time-dependent history of location and orientation of the sensor. A scene sampling module generates an array of query ray origins and directions from the view point through the image plane to obtain radiance values from other testbed modules. Blurring effects, including those from diffraction, aberrations, detector spacing, and digitization are accounted for by using results from the validated NVTherm model. In this way, the sensor system's modulation transfer function is imposed on the image. In addition, atmosphere effects are incorporated through the use of external scattering models. If necessary, the resulting radiance image is re-sampled at desired pixel locations. Finally, the detector response characteristics are applied to the radiance image for computation of signal voltages. A noise voltage is then added and the digitization process simulated to produce the final sensor output synthetic image. The model is implemented in C++ using object-oriented programming techniques that allow for flexible extension of the simulation to different types of sensors and geometries. Model design goals, techniques, components, and specific image synthesis algorithms implementations are discussed along with the presentation of example results.
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