An enhanced Cramér-Rao bound weighted method for attitude accuracy improvement of a star tracker

Abstract

This study presents a non-average weighted method for the QUEST (QUaternion ESTimator) algorithm, using the inverse value of root sum square of Cramér-Rao bound and focal length drift errors of the tracking star as weight, to enhance the pointing accuracy of a star tracker. In this technique, the stars that are brighter, or at low angular rate, or located towards the center of star field will be given a higher weight in the attitude determination process, and thus, the accuracy is readily improved. Simulations and ground test results demonstrate that, compared to the average weighted method, it can reduce the attitude uncertainty by 10%-20%, which is confirmed particularly for the sky zones with non-uniform distribution of stars. Moreover, by using the iteratively weighted center of gravity algorithm as the newly centroiding method for the QUEST algorithm, the current attitude uncertainty can be further reduced to 44% with a negligible additional computing load.