Spacecraft Orbital Maneuver Detection Using Adaptive Multi-Feature Criteria

Abstract

To address the unstable detection of weak orbital maneuvers from publicly available Two-Line Element (TLE) data affected by natural perturbations, orbit-determination errors, outliers, and irregular update intervals, an adaptive multi-feature maneuver-detection method is proposed. The method incorporates a dominant J2 perturbation correction into the computation of the mean semimajor axis and combines semimajor-axis variation, eccentricity variation rate, and local dispersion of mean motion. A two-stage outlier-processing scheme, iterative background-noise estimation, and an adaptive switching mechanism based on the sampling interval are further introduced. Multi-object simulations for low- and high-altitude satellites show that the average detection accuracies for along-track maneuvers are 94.47% and 93.95%, respectively, while those for radial maneuvers are 92.83% and 93.26%, respectively. The proposed method demonstrates stable detection performance and good applicability across different orbital altitudes and maneuver directions.