An SSA-to-ADR Uncertainty Propagation Pipeline for Tether-Net Debris Capture Mission Planning

Tether-net systems represent a leading technology for the Active Debris Removal (ADR) of non-cooperative space objects; however, a fundamental operational gap persists between the discipline of Space Situational Awareness (SSA) and the mechanics of net-based capture. No existing framework propagates the observational uncertainties inherent to SSA data through net deployment dynamics to yield operationally actionable capture probability estimates. This paper addresses that gap by proposing an end-to-end SSA-to-ADR uncertainty propagation pipeline that treats tether-net debris capture as a probabilistic decision problem under observational uncertainty. Characterization of the full debris-state covariance from TLE-derived orbital uncertainties and photometric light-curve spin-state estimates; linear covariance propagation and Monte Carlo sampling through a lumped-parameter tether-net deployment dynamics model to the ejection epoch; and construction of a capture probability surface over the ejection parameter space that quantifies expected capture success as a function of observable data quality. The methodology is developed and exercised using Telkom-3, a defunct Indonesian satellite with concurrent photometric observations from Zimmerwald Observatory. The role of ground-based geographically distributed SSA networks in reducing state uncertainty and improving capture reliability is explicitly quantified. In the present implementation, the framework’s rotational-phase coupling is exercised in its conservative, uniform-phase limiting case; the architecture is designed to accommodate the spin-period-dependent phase concentration suggested by the photometric dataset as a direct extension. The proposed framework establishes a principled, transferable, and traceable methodology for probabilistic ADR mission planning conditioned on actual observational campaign quality.