Raymond Wright, BAE Systems; Geoffrey Lake, Icebox Engineering; Thomas Drouillard, BAE Systems; Andrew Wernersbach, BAE Systems; Kedar Naik, BAE Systems; Michael Dittman, BAE Systems; Matthew Tooth, BAE Systems
Keywords: Space Domain Awareness, Hyperspectral, Characterization, Space-Based Assets, Cislunar
Abstract:
Hyperspectral sensing is an emerging technology that could enable characterization and discrimination of Resident Space Objects (RSO)s with the need for resolved imagery or detailed light-curves over many phase angles. Hyperspectral imaging, which captures a wide range of wavelengths across the electromagnetic spectrum, can provide a richer, more comprehensive view of space objects compared to traditional single-band or multispectral methods. Hyperspectral remote sensing has been widely used in terrestrial remote sensing of RSOs. Instruments such as the Ohio State Infrared Imager/Spectrometer (OSIRIS) (1999 – 2018)[1] and the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) (2020 – current)[2] provide medium to high spectral resolution. These instruments can provide precise spectral detail for material identification enabling object identification and classification. Artificial Intelligence/Machine Learning (AI/ML) has demonstrated the ability to use multi-spectral information to classify active, passive, and space debris RSOs[3]. For this discussion, classification is defined as the ability to determine the type of RSO based off its light signature. Identification is using this information, and more, to determine the specific RSO (Hubble, Starlink 1, Starlink 376, etc.) However, ground-based hyperspectral instruments have severe shortcomings which a space-based sensor can bypass to improve the SSA community’s charter.
Hyperspectral imaging from the ground is often limited by atmospheric conditions and location. Atmospheric effects like cloud coverage inhibit observational opportunities. The atmospheric window restricts instrument designs to specific bandwidths, limiting the capture of useful information. For example, OSIRIS was designed to capture light between the visible and near-infrared (0.95 – 2.4 micrometers), and PEPSI is designed only for the ultra-violate to visible spectrum (0.38 – 0.91 micrometers). These wavelengths center on the reflective side of the atmospheric window. Another disadvantage is location. Ground-based systems are stationary. They require very large optics, sometimes cryocooled, which prohibits moving the systems. The PEPSI instrument is attached to the Large Binocular Telescope (LBT) Observatory located in Mt. Graham in Arizona. Timely tracking and dissemination of information of RSOs can only be achieved when the RSO is overhead.
This paper will explore the advantages a space-based hyperspectral sensor will bring to the community. Using validated models, we will generate signatures for additional classes of objects and leverage the prior work[3] to further improve on the windows that offer the most information for classification; then detail some notional design reference missions to limit the design trade space of a study. Various design parameters like range, aperture, spectral resolving power will be traded and assessed. This feeds into an assessment of the design option spaces which can provide an estimate of the TRL of technologies necessary to make one or more of the sensor designs realizable. The result will show where a space-based SSA asset can complement existing ground-based architectures and surpass current capability.
With the ability to offer continuous, global coverage, precise object tracking, and detailed material characterization, adding space-based hyperspectral instruments to complement our ground-based telescopes would significantly enhance our ability to monitor space objects, detect potential threats, and improve overall space safety. As space traffic and debris continue to increase, the need for such advanced capabilities will only grow, making space-based hyperspectral SSA missions a critical asset to the global space community.
[1] The Ohio State University, “Ohio State Infrared Imager/Spectrometer (OSIRIS)”, Ohio State InfraRed Imager/Spectrometer (OSIRIS) | Department of Astronomy, (2025)
[2] Large Binocular Telescope Observatory, “PEPSI”, PEPSI : Science Ops – Large Binocular Telescope Observatory (LBTO), (2025)
[3] Naik, K., Wernersbach, A., Robinson, A., Nilson, M., Wiemokly, G., Tooth, M., Wright, R., “ML-Driven Optimal Design of Multispectral Instruments for the Characterization of Resident Space Objects” in [Proceedings of the Advanced Maui Optical and Space Surveillance (AMOS) Technologies Conference] (2024)
Date of Conference: September 16-19, 2025
Track: Space-Based Assets