Stefan Doucette, InTrack Radar Technologies; Kaitlyn Raub, InTrack Radar Technologies; William J. Mandeville, InTrack Radar Technologies; Tim McLaughlin, InTrack Radar Technologies
Keywords: cislunar, xgeo, motion hypothesis, velocity search, algorithm, discovery
Abstract:
The expanding cislunar domain presents unprecedented challenges for Space Situational Awareness (SSA), particularly when spacecraft custody is lost and objects must be rediscovered without a priori orbital knowledge. Traditional telescope tracking methods to enhance signal fail in these scenarios because they rely on known position and velocity information to enable long exposure times and frame stacking techniques.
Building on previous work presented at AMOS 2024, this paper introduces an automated enhancement to the parametric motion hypothesis algorithm for discovering faint satellites in cislunar space. The new system incorporates quantifiable metrics in a feedback loop to automatically determine optimal motion hypotheses and maximize signal-to-noise ratios without human intervention. This advancement enables seamless integration into nightly telescope operations at Pine Park Observatory, located in Colorado, providing an operational capability for autonomous cislunar object discovery. Results demonstrate successful detection of spacecraft at distances up to 1.26 million kilometers from Earth, with position accuracies averaging 0.9 pixels and velocity accuracies of 0.02 pixels per frame, using as few as 5-11 images per detection.
Date of Conference: September 16-19, 2025
Track: Cislunar SDA