A new method of star catalog optimization for multi-FOV star sensor

A new method of star catalog optimization for multi-FOV star sensor is presented. Compared with single-FOV star sensor, multi-FOV star sensor has higher attitude accuracy and update frequency. By conducting Monte Carlo Simulation and labelling stars based on magnitude, the optimization of guide star catalog reduces the size of the catalog and improves the uniformity of the catalog, which is more suitable for multi-FOV star sensor. Test results show that the accuracy rate of the star recognition algorithm using the new catalog is higher than 95%, which can meet the requirement of the actual design. Further, in respects of storage space of the star catalog and the search speed, the new method of catalog optimization based on simulation and marking is superior to other methods under the same conditions.