Data matching and association based on the arc-segment difference method

In response to the issue of fuzzy matching and association when optical observation data is matched with the orbital elements in a catalog database, this paper proposes a matching and association strategy based on the arc-segment difference method. First, a matching error threshold is set to match the observation data with the known catalog database. Second, the matching results for the same day are sorted based on target identity and observation residuals. Different matching error thresholds and arc-segment dynamic association thresholds are then applied to categorize the observation residuals of the same target across different arc segments, yielding matching results under various thresholds. Finally, the orbital residual is computed through orbit determination (OD), and the position error is derived by comparing the OD results with the orbit track from the catalog database. The appropriate matching error threshold is then selected based on these results, leading to the final matching and association of the fuzzy correlation data. The experimental results show that the correct matching rate for data arc segments is 92.34% when the matching error threshold is set to 720″, with the arc-segment difference method processing the results of an average matching rate of 97.62% within 8 days. The remaining 5.28% of the fuzzy correlation data are correctly matched and associated, enabling the identification of orbital maneuver targets through further processing and analysis. This method significantly enhances the efficiency and accuracy of space target cataloguing, offering robust technical support for the dynamic maintenance of the space target database.