Generation of guide star catalog for the all-time three-FOV star sensor applied on airborne platforms

The guide star catalog plays a crucial role in the star sensor, impacting the system's star identification speed and attitude measurement accuracy. Currently, the generation method for the guide star catalog is well developed for star sensors used on satellites. However, the inter-FOV guide star catalog for the all-time three-FOV star sensor still faces challenges such as excessive storage requirements, non-uniform distribution of guide stars, and incompleteness. Aiming at these problems, this paper proposes a generation method for the inter-FOV guide star catalog. Initially, a method for estimating instrument magnitudes in the short-wave infrared (SWIR) band is proposed and validated. Then, a theoretical model of the all-time three-FOV star sensor is established, and its extreme detection magnitudes are analyzed. Subsequently, the guide stars are initially selected using the improved spherical spiral method (ISSM) based on their uniformity and brightness, followed by the combination of the generalized regression neural network (GRNN) and the Monte Carlo method to generate the guide star catalog. Finally, it is verified by simulation experiments that the proposed method improves the uniformity and completeness while reducing the storage capacity.