Optical imagery from space-based telescopes is one of the most valuable tools for understanding various large and small-scale processes on planetary bodies. Whether in orbit around the Earth or another body in the solar system, it is desirable to obtain the highest resolution imagery possible of the central body. The traditional approach to achieving higher resolution imagery is to increase the size of the optical payload’s aperture. However, larger aperture payloads become prohibitively difficult to manufacture and excessively expensive to design, build, launch, and operate. Application of rotating synthetic apertures (RSA), which is a form of dilute aperture imaging system, to space telescope designs have the potential to unlock the design space of low mass and cost, high resolution space telescopes. RSAs employ a high aspect ratio rectangular aperture that is spun about its principal optical axis. A complete image is formed after a 180° rotation during which multiple frames are acquired to fully sample the imaging system’s optical transfer function. The sampling strategy, which involves the number of individual frames captured and the rate of spin about the principal optical axis, is a function of the RSA’s aperture dimensions. The purpose of this work is twofold. First, an expression for resolution in reconstructed images is derived as a function of orbital altitude, RSA aperture dimensions, and amount of spatial oversampling of the target scene. This expression is used to predict potential science data return for a given orbit, RSA design, and sampling strategy. Second, a multi-objective optimization analysis is performed between reconstructed image resolution and optical telescope assembly (OTA) cost from which a Pareto frontier is defined. This analysis informs an ensuing discussion of optimal RSA aperture dimensions for achieving optimal conditions in resolution and cost. Additionally, the effects of different RSA aperture dimensions on sampling strategies are discussed. Based on these results and discussions, a high-level design for an RSA demonstration mission is proposed. Additional presentation content can be accessed on the supplemental content page.
Simultaneously prototyping several sensing architectures is costly and time consuming. Therefore, a modeling pipeline that is capable of both nanoscale electromagnetic wave and macroscale ray tracing simulations for the design, performance prediction, and validation of future AR/VR/MR sensing modalities is crucial. However, current end-to-end sensor modeling pipelines use several software packages with cumbersome interfaces between scene radiometry definition, macro optical component design, and photonics component design. In our paper, we demonstrate, implement and validate a sensor modeling pipeline with streamlined interfaces and modular component definition capabilities. The pipeline is composed of Ansys Speos for source radiometry and geometry definition, Zemax OpticStudio for camera lens system definition, and Lumerical FDTD for image sensor definition. This end-to-end pipeline is used to model a camera system developed at Reality Labs and designed for AR/VR/MR applications. The first section of this paper describes the camera system modeled in the pipeline. Validation efforts for the pipeline involved comparing simulated images, obtained from inverse Monte Carlo ray propagation simulations, to experimentally collected images with the corresponding hardware. Specifically, the distortion and modulation transfer function (MTF) were determined for the simulated and experimentally collected images using ImaTest image quality software. The second section of this paper describes these validation efforts and the obtained results. The modularity of the modeling pipeline is highlighted throughout the paper for its applicability to various sensing architectures of interest to AR/VR/MR technologies.
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