Integration of optomechanical system models with DIRSIG

Keegan S. McCoy; John P. Kerekes; Scott D. Brown; Adam A. Goodenough; Rolando V. Raqueño; Jared D. Van Cor; Ryan G. Irvin

doi:10.1117/12.2320641

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17 September 2018 Integration of optomechanical system models with DIRSIG

Keegan S. McCoy, John P. Kerekes, Scott D. Brown, Adam A. Goodenough, Rolando V. Raqueño, Jared D. Van Cor, Ryan G. Irvin

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Proceedings Volume 10743, Optical Modeling and Performance Predictions X; 1074304 (2018) https://doi.org/10.1117/12.2320641
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

Stray light, any unwanted radiation that reaches a focal plane, presents a significant challenge for both airborne and satellite remote sensing systems by reducing image contrast, creating false signals or obscuring faint ones, and ultimately degrading radiometric accuracy. These detrimental effects can have a profound impact on the usability of collected data, which must be radiometrically calibrated to be useful for scientific applications. Understanding the full impact of stray light on data scientific utility is of particular concern for lower cost, more compact satellite systems which inherently provide fewer opportunities for stray light control. To address these concerns, we present a general methodology for integrating an optomechanical system model with the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The results reported in this paper describe the collection of necessary raytrace data from an optomechanical system model (in this case, using FRED Optical Engineering Software), and also include the initial demonstration of the integration method by imaging DIRSIG test scenes. By integrating a high-fidelity optomechanical system model with a physics-driven, synthetic image generation model like DIRSIG, we are now able to explore system trade studies and conduct sensitivity analyses on parameters of interest, including those that influence stray light, by analyzing their effects on realistic test scenes. This new capability further aids in demonstrating the quantitative linkage between system trade studies and impact to scientific users, which will enhance the writing of system requirements.

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Keegan S. McCoy, John P. Kerekes, Scott D. Brown, Adam A. Goodenough, Rolando V. Raqueño, Jared D. Van Cor, and Ryan G. Irvin "Integration of optomechanical system models with DIRSIG", Proc. SPIE 10743, Optical Modeling and Performance Predictions X, 1074304 (17 September 2018); https://doi.org/10.1117/12.2320641

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