Abstract This paper focuses on the track-to-object association problem based on the two-line element (TLE) set. A five-step track-to-object association algorithm is designed for the radar observation data. First, for all objects in the TLE set, their orbits are propagated and stored with a step of 10?min. Then the orbital position at an arbitrary epoch can be obtained through the interpolation algorithms. Second, for tracklets longer than 60?s, the extended Laplace method is implemented to determine the orbital elements. Third, the semimajor axis, eccentricity, inclination, and the right ascension of the ascending node are used to filter the TLE sets. More than 90% of the objects can be filtered, improving the association efficiency significantly. Fourth, a first-order association process is implemented to get candidate objects, with the difference between the observed positions and the TLE orbit positions as a metric. Finally, considering the measurement error and the TLE orbit uncertainty, an uncertainty-based final association process checks the candidate objects and gives the final association result. The proposed approach is tested with simulated and observed data. The true-positive rate is higher than 99.5%, while the false-positive rate and the false-negative rate are both lower than 0.1%.
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