Star Tracker Accuracy Improvement and Optimization for Attitude Measurement in Three-Axis

High precision attitude measurement systems obviate the need for the beacon from the receiver making it possible for the spacecraft to beam a laser communications signal to a ground station without the ground station advertising its location. The research presented targets new detection and estimation methods to improve the accuracy in locating stars on a focal plane detector, and an understanding of the effects of changes in the optics design parameters and aberration, including defocus, on the navigation solution itself. This understanding can lead to an optimization of the attitude solution with respect to those optics realm parameter changes. The methodology discussed includes the development of a model of a current star tracker system. Using this model, multiple algorithms are implemented, including a multi-hypothesis method (MHT), to detect and estimate the position of the stars on the focal plane detector. It will be shown that using the MHT for detection and estimation, a greater accuracy can be found for each star estimation from more traditional detection and estimation algorithms. The approach then uses the model to develop statistics of the star tracker and the attitude estimation outputs to understand the accuracy, or variance, of the system's attitude solution. This solution is repeated for a range of defocus aberration, and a lower limit to the variance of the attitude solution is shown. A Cramer Rao lower bound solution is derived for the star tracker system and the results are compared to the Monte Carlo analysis from the model and shown to correlate very well. The approach uses a star image not as a Gaussian spot on the focal plane as done in previous work, and use of an image that includes the effects of aberrations of the optic system, and the effects of under-sampling and noise from the focal plane detector as well. Analysis includes exploring a star tracker's accuracy improvement through the combination of focus error and under-sampling effects alone, possibly contradicting conventional wisdom and approaches.