Randa Qashoa, York University; Matthew Driedger, Magellan Aerospace; Ryan Clark, C-CORE; Paul Harrison, Magellan Aerospace; Michael Berezin, Magellan Aerospace; Regina Lee, York University; Andrew Howarth, University of Calgary
Keywords: SSA, Machine Learning, Optical Space Surveillance, Optical Systems, Orbit Determination
Abstract:
The proliferation of resident space objects (RSOs) in the near-Earth realm requires increased monitoring capabilities to ensure the safety and security of space-based infrastructure. Ground-based systems, using both radar and narrow field optical systems, currently form the backbone of this monitoring-and-follow-up capability, supported by space-based surveillance missions. The latter have the potential to vastly increase coverage of LEO orbital regimes, being unaffected by weather or geographic considerations, but their implementations tend to be optimized for GEO, MEO, and HEO object tracking.
This paper presents the solutions for LEO object detection that Magellan Aerospace and its collaborators at York University, C-CORE, and the University of Calgary have been developing since 2017, using commercial optical sensors, and in particular star trackers. Although small in aperture, their wide fields-of-view (FOV) of ~20° across or more make star trackers ideal for background sky object monitoring. Additionally, their coarse pixel resolution reduces signal loss from streaking due to high relative angular rates in LEO. The real potential of these commercial-off-the-shelf (COTS) sensors, however, is their ubiquity – currently employed by hundreds of spacecraft for attitude determination. If dual-purposed for RSO monitoring, the collective coverage offered by these “backyard orbiting observatories” in LEO would be immense.
With funding from Canada’s Department of National Defence, Magellan and its partners are implementing a prototype system as part of a project called SPACEDUST (Special Processes and Advanced Computing Environment for Detection, Unambiguity, Surveying, and Tracking). The SPACEDUST-Optical prototype uses Fast Auroral Imager (FAI) imagery from the CASSIOPE satellite to demonstrate the full cycle of RSO prediction, detection, identification, and orbital refinement. The FAI FOV and detection capability are analogous to those of star trackers, and its images contain many RSOs of interest, especially in polar regions that are difficult to access by ground systems.
The prototype system includes regular imaging of RSOs of interest using the FAI, together with custom software suites that predict RSO access times, simulate RSO images, detect RSOs in images, and then identify the detected RSOs. The results from the SPACEDUST-Optical prototype are compared against truth data from RSOs that have publicly-available ephemeris. Applications for this technology include, but are not limited to: monitoring for new or previously unknown RSOs; orbit refinement of RSOs that are detected by other systems and shown to be a potential collision risk; light curve and large-scale reflectivity analysis; and disambiguation of debris from collision or break-up events.
Dual-purposing star trackers, and similar COTS sensors, for space situational awareness (SSA) presents both technical and logistical challenges. For example, downlink capacity limits the quantity of images that can be practically sent during ground station passes. This bandwidth challenge is addressed using SPACEDUST’s onboard RSO detection capability, using machine learning technology, which vastly reduces the data needed to be downlinked. This detection technology is currently being tested on the ground using FAI imagery as part of the SPACEDUST-Optical prototype, but in a form that is imager-agnostic and that can be readily implemented onboard for future platforms using other wide-FOV sensors.
As the RSO population continues to increase, SSA platforms in space are becoming more critical to track and study these objects. The SPACEDUST-Optical prototype has already demonstrated the tremendous benefit that a single space-based wide-FOV sensor can add to the SSA picture. By utilizing COTS star trackers and other wide-FOV imagers, the SPACEDUST-Optical technology can dramatically increase SSA coverage, thereby making the LEO environment safer and more sustainable.
Date of Conference: September 19-22, 2023
Track: SDA Systems & Instrumentation