Improving star tracker centroiding performance in dynamic imaging conditions

We present an assessment of various image thresholding and centroiding algorithms to improve star tracker centroiding accuracy at moderate slew rates (<;10°/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°/s. Most of star detection algorithms in literature are designed to work in stationary conditions. We evaluate a number of algorithms from literature and measure their performance in motion. The performance of the algorithms are assessed using simulations. The primary performance metrics are false positive ratio, and false negative ratio of star pixels. We introduced a new algorithm for star acquisition in moderate slew rates that combines positive features of existing algorithms. This algorithm increases the star detection accuracy in moderate slew rates and it is robust to stray light.