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Space-Domain Awareness (SDA) via remote thermal imaging, where thermal-waveband EO/IR sensors are employed to observe orbiting satellites, has benefits over conventional visible/short-wave imaging. For example, LWIR sensors provide capability for both daytime and nighttime imaging, since temperature emissions and reflections are the basis of such observation (as opposed to optical sensors which rely on reflected light). To understand the capability that thermally dominant wavebands such as LWIR and MWIR can play in SDA, a robust simulation capability must be developed to predict signatures across the relevant spectrum. The computational complexity required for radiative transfer simulation is typically greater for satellite-focused thermal modeling in comparison to shortwave, reflected light-dominant wavebands. In this work, we employ MuSES to demonstrate the prediction of both internal and external temperature distributions for 3D satellite models. MuSES uses dynamic orbital boundary conditions to simulate transient solar loading, thermal radiation from Earth and to space, as well as radiative and conductive heat transfer from internal components such as electronics. Additionally, the coupled thermal/electrical multi-physics solvers in MuSES can incorporate realistic solar panel efficiency and battery cell charge/discharge cycling. Surfaces are attributed with spectral optical surface properties across the waveband(s) of interest to generate radiance maps via BRDF-based ray tracing of the predicted 3D temperature distributions. This allows radiometric signal levels of both the target and background, and subsequently contrast metrics of interest, to be generated with sensor simulations of space-based imaging platforms. Signature prediction is the primary output of this process, and in this study, we use our described methodology to demonstrate the inclusion of solar panel efficiency, battery charging/discharging and internal heat sources impact surface temperature distributions and infrared signatures during observations of satellites in LEO and GEO. A sensitivity study is performed to determine the significance that several satellite design choices can have on resultant signatures.
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