VLSI implementation of star detection and centroid calculation algorithms for star tracking applications

Nowadays, hardware implementation of image and video processing algorithms on application specific integrated circuit (ASIC) has become a viable target in many applications. Star tracking algorithm is commonly used in space missions to recover the attitude of the satellite or spaceship. The algorithm matches stars of the satellite camera with the stars in a catalog to calculate the camera orientation (attitude). The number of stars in the catalog has the major impact on the accuracy of the star tracking algorithm. However, the higher number of stars in the catalog increases the computation burden and decreases the update rate of the algorithm. Hardware implementation of the star tracking algorithm using parallel and pipelined architecture is a proper solution to ensure higher accuracy as well as higher update rate. Noise filtering and also the detection of stars and their centroids in the camera image are the main stages in most of the star tracking algorithms. In this paper, we propose a new hardware architecture for star detection and centroid calculation in star tracking applications. The method contains several stages, including noise smoothing with fast Gaussian and median filters, connected component labeling, and centroid calculation. We introduce a new and fast algorithm for star labeling and centroid calculation that needs only one scan of the input image.