This research is aimed to improve star tracker performance in presence of dynamic conditions. It offers an assessment of various image thresholding and centroiding algorithms to improve star tracker centroiding accuracy at moderate slew rates (< 10 0=s). Star trackers generally have arc-second accuracy in stationary conditions, however their accuracy degrades as slew rate increases.
In dynamic conditions, blur effects add to the challenges of star detection. This work presents an image processing algorithm for star images that preserves star tracker detection accuracy and is able to detect dim stars up to slew rates less than 10 0=s. A number of algorithms from literature were evaluated and their performance in motion and simulations were measured. The primary performance metrics are false positive ratio, and false negative ratio of star pixels. This Work introduced a new algorithm for star acquisition in moderate slew rates that combines positive features of existing algorithms.