Presentation + Paper
20 August 2020 The Venus Emissivity Mapper (VEM): advanced development status and performance evaluation
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Abstract
The Venus Emissivity Mapper (VEM) has a mature design with an existing laboratory prototype verifying an achievable instrument SNR of well above 1000 as well as a predicted error in the retrieval of relative emissivity of better than 1%. VEM will provide a global map of surface composition as well as redox state of the surface by observing the surface with six narrow band filters, ranging from 0.86 to 1.18 μm. Continuous observation of Venus’ thermal emission will place tight constraints on current day volcanic activity. Eight additional channels provide measurements of atmospheric water vapor abundance as well as cloud microphysics and dynamics and permit accurate correction of atmospheric interference on the surface data. A mission combining VEM with a high-resolution radar mapper such as the ESA EnVision or NASA VERITAS mission proposals will provide key insights in the divergent evolution of Venus. Here we discuss the approach and results of the evaluation of the VEM sensor’s radiometric performance by an analysis of the corresponding signal processing chain. The passage of a simulated radiometric scene signal of the planet Venus through the VEM optics, detector, analog and digital electronics has been evaluated based on a theoretical model of the system. The goal was to verify the overall system performance with respect to the scientific requirements. This is building on our preliminary evaluation of the VEM laboratory prototype and confirms that the VEM design has significant performance margins.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Helbert, T. Säuberlich, Melinda Darby Dyar, Conor Ryan, Ingo Walter, Jean-Michel Reess, Yaquelin Rosas-Ortiz, Gisbert Peter, Alessandro Maturilli, and Gabriele Arnold "The Venus Emissivity Mapper (VEM): advanced development status and performance evaluation", Proc. SPIE 11502, Infrared Remote Sensing and Instrumentation XXVIII, 1150208 (20 August 2020); https://doi.org/10.1117/12.2567634
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Cited by 1 scholarly publication.
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KEYWORDS
Venus

Signal to noise ratio

Sensors

Optical filters

Image filtering

Bandpass filters

Linear filtering

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