James Herring, Slingshot Aerospace; Alex Ferris, Slingshot Aerospace; Jack Wickstrom, Slingshot Aerospace; Carl Steinhauser, Slingshot Aerospace; Ari Larson, Slingshot Aerospace; Jeffrey Shaddix, Slingshot Aerospace; Belinda Marchand, Slingshot Aerospace
https://doi.org/10.64861/UGKX2161
Keywords: Electro-optical Systems, Sensor-systems, Gimbaled Optical Systems, Ground-based Systems, Daytime Imaging, Imaging, Image Processing, Tasking, Launch Tracking, Reentry Tracking, Low-altitude Tracking, LEO, LEO Custody, Space Domain Awareness
Abstract:
A fundamental requirement of space domain awareness (SDA) is the ability to consistently track resident space objects (RSOs) as they orbit and operate within the space environment. The difficulty of tracking a specific RSO varies significantly based on a wide range of characteristics, e.g., orbital parameters, object size, mission operations, and accessibility of owner/operator ephemerides. Ground-based electro-optical (EO) systems and techniques for detecting RSOs with varying characteristics are essential tools in the SDA toolbox, and the continual development of novel techniques for increasing the portion of trackable RSOs is essential as their number and variety proliferate.
One class of RSOs which has proven consistently difficult to track is objects with high in-track uncertainty in low earth orbit (LEO) or at perigee of a highly elliptical orbit (HEO), i.e., objects with well-known orbital planes but whose positions along their orbits is uncertain. For this class, potential sources of in-track uncertainty include launch nominal errors, poorly modeled drag forces due to atmospheric density uncertainty, certain classes of maneuvers, and poor cueing based on stale state information. Existing solutions to tracking such objects include optical fence systems and related uncued matched filter detection algorithms [1]. However, these systems rely on wide field-of-view (FOV) sensors and relatively small apertures which limits them to nighttime operability and consequently restricts their viewing opportunities to RSOs passing through terminator conditions. For many RSOs of interest, these limitations either significantly reduce or eliminate the ability of optical fence systems to observe these RSOs depending on their orbits, the season, and sensor network alignment. In contrast, cathemeral (both day and night operational) EO systems provide increased viewing opportunities for this class of RSOs, but existing cathemeral EO solutions have comparatively narrow FOVs and rely on gimbaled, rate-tracked data collection. This lowers the probability that RSOs with high in-track uncertainty will be within the system’s FOV for a given collection attempt [2].
In this work, we explore overcoming these challenges by combining cathemeral EO systems with synthetic rate tracking (SRT). Various SRT techniques have been published in-depth for near-Earth object and space surveillance applications [3]. The authors’ variant, Synthetic In-track Fence Tracking (SIFT), collects data using a “fence” scan pattern to search a theoretically unlimited amount of in-track space by continuously accounting for the precession of an RSO’s orbit as seen from the location of the collecting system. Data collection leverages the high-framerate capabilities of cathemeral EO systems and an adaptive stacking algorithm to mitigate the motion blur of LEO objects passing through the system FOV. This maximizes detectability within the constraints of the scan pattern and minimizes detectability loss compared to rate-tracked collections. Through this approach, SIFT removes both the requirement for terminator viewing that restricts uncued LEO optical fence systems and the limitation of a narrow FOV that restricts rate-tracked collections from cathemeral EO gimbaled systems.
In this paper, we provide an analysis illustrating the dominance of in-track error for the class of RSOs of interest and quantifying the increased viewing opportunities for this class of RSOs when using daytime-capable EO systems. Using this as motivation, we then present a technical overview of SIFT. This overview includes analysis of SIFT’s detectability loss compared to rate-tracked collections as a function of sensor frame rate. Lastly, we present results demonstrating SIFT for mission-relevant scenarios including launch tracking, reentering RSOs, low altitude/high drag RSOs, and RSOs with poor cueing due to stale states or maneuvers. Results will be presented from both daytime and nighttime collections and mix compelling anecdotal SIFT collections with broader analysis compiled over many collections.
Date of Conference: September 15-18, 2026
Track: Space Domain Awareness