Adaptive dynamic adjustment star identification threshold estimation for a terrestrial star tracker

Abstract

As the criterion to determine whether stars are identified, the star image identification matching threshold is an important parameter in terrestrial star trackers. It not only determines the identification success rate, but also affects the redundant matching quantity and identification efficiency. This paper focuses on the problem that the identification efficiency of terrestrial star trackers is restricted by inappropriate matching thresholds and presents an adaptive dynamic adjustment star identification threshold model. Compared to the existing matching threshold, the presented model clarifies the transformation of observation star angular distance errors and dynamically estimates the corresponding identification threshold as the variation of observation angular distances and attitudes. Therefore, we believe it completes the star identification with an excellent redundant matching quantity and identification efficiency. Numerical simulation and night sky experimental results showed that the identification efficiency was improved by more than 46.54% and 22.61%, respectively, while the identification success rate remained at 100%.