ARCC Imaging with the WITHUS System

The purpose of this project is to develop a parameterized model for commercial float glass that can be used as a reflective surface with an automated characterization and correction method to reconstruct images observations of dim objects using an optical system capable of hardware and software-based distortion corrections. A physical model of the glass will be developed leveraging commercial standards and practices to constrain the physical parameters of the glass, and embed physical distortions based upon a parameterized model. This surface will be characterized using a secondary system that leverages a multi-stage approach, utilizing laser reflections, long term optical metrology of reflections, and in-camera detection and tracking of point sources during observations to an eighth of the wavelength. The distorted wavefront due to the glass surface and other factors will be corrected within an optical system utilizing a combination of hardware and AI/ML based corrections utilizing a lensless camera. A simulation will be developed to analyze the optical behaviors of the systems to refine and improve the proposed optical system design. A system capable of observing and characterizing dim objects utilizing the thousands of square meters of commercial float glass can drastically expand the size of a space domain awareness network using a fraction of the cost of large-scale radar and optical observatories. The challenge of this approach is significant due to observations off an imperfect surface and in an optically challenging environment results in a highly noisy and distorted imagery. Successful implementation of the surface characterization and optical system will result in a leap forward in algorithmic and hardware approaches for related problems. The success of the approach will be defined by the accuracy of the glass surface characterization method, both spatial and temporal, and the ability of the system to observe dim, weakly reflecting low earth orbit satellites and distant geostationary satellites in either optical or near infrared. A secondary metric is to reduce the complexity of the system by replacing hardware distortion corrections with in-sensor based algorithmic distortions without reducing system performance.