Effect of Compressive Sensing Star Image on Attitude Determination

The star tracker is the currently most accurate sensor which determines the absolute three-axis attitude of a spacecraft. The emergence of compressive sensing (CS) theory provides the star tracker with a novel approach that can perform attitude determination by low data rate. Thus, there exists a common problem that whether the star image acquired by CS sparse reconstruction can give the correct attitude with regard to the acceptable accuracy. In order to address the problem, this paper analyzes the effect of CS reconstructed star image on attitude determination and conducts statistical simulations with respect to different noise cases and compression ratios. The results show that the CS method for star tracker can keep the accuracy of attitude determination in noise cases to a large extent and the accuracy approaches to the traditional method with an increasing compression ratio, which proves the feasibility of applying CS theory in star tracker.