https://www.mdu.se/

Hyperspectral thermal imagers provide characteristic information that conventional spectral imagers cannot offer. The proliferation of space assets and debris will require “eyes in the sky'' to track objects effectively. The current estimates as of 2022 state that more than 27,000 pieces of orbital debris are tracked by the Department of Defense’s global Space Surveillance Network (SSN). This number is expected to double in the next ten years with 57,000 satellites expected to be launched by 2029. Ground-based assets will not be able to track this vast number of orbital debris, and space-based monitoring capabilities will have to complement the tracking of assets and debris in the years to come. In this work, we present the Hyperspectral Thermal Imager (HyTI) CubeSat design, initially developed for Earth Observation, that can be adapted for Space Situational Awareness (SSA) applications with machine learning algorithms for fast object detection. With new advances in machine learning hardware and software, the categorization of orbital objects can help reveal features such as geometry, thermal signature, and size, among others. For example, spectral signatures can be leveraged to identify plumes of thrusters and unique characteristics of various materials used in different objects. HyTI is a 6U CubeSat funded by NASA’s Earth Science Technology Office (ESTO) In-Space Validation of Earth Science Technologies (InVEST) program. HyTI demonstrates how high spectral and spatial longwave infrared image data can be acquired from a 6U CubeSat platform. The long wave infrared detector uses a push-broom technique for producing accurate spectral and spatial data for moving targets. HyTI will demonstrate advanced on-orbit real-time data processing and the creation of scientific and operational data products. The payload uses aspatially modulated interferometric imaging technique to produce spectro-radiometrically calibrated image cubes, with 25 bands between 8-10.7 microns. The HyTI performance model indicates narrow band NEDTs of < 0.3 K. The small form factor of HyTI is made possible via the use of a no-moving-parts Fabry-Perot interferometer developedby the Hawaiʻi Institute of Geophysics and Planetology (HIGP) at the University of Hawaiʻi at Mānoa (UHM), and a Jet Propulsion Laboratory (JPL) cryogenically cooled High Operating Temperature (HOT) Barrier Infrared Detector (BIRD) focal plane array (FPA) technology. The level 0 (L0) data rate of the HyTI instrument is large. As a result, HyTI processes data from L0 to level 1 (L1, calibrated spectral radiance cubes) onboard. This is achieved using an advanced radiation-tolerant heterogeneous computer, the Unibap iX5-100 space computer, which offers CPU, GPU, and FPGA processing capability and has the option to add one or more neural network accelerators [12]. In this way, the L0 data volume is reduced by a factor of 13 before transmission to the ground as L1 data. Fully equipped, the iX5-100 can achieve several trillion computational operations per second (TOPS), which is essential for on-orbit detection of objects [13]. In this paper we provide an overview of the HyTI design and how it can be adapted for SSA observations and applications. We expand on the onboard data reduction and object detection approach, then provide an overview of the SpaceCloud Framework containerization of mission management and data applications.