Adaptive Neural Star Tracker Calibration for Precision Spacecraft Pointing and Tracking

Abstract The star tracker is an essential sensor for precision pointing and tracking in most 3-axis stabilized spacecraft. In the interest improving pointing performance by taking advantage of dramatic increases in flight computer power and memory anticipated over the next decade, this paper investigates the use of a neural net for adaptive in-flight calibration of the star tracker. Estimation strategies ate given for cases when the spacecraft attitude is both known and unknown.