On the Starspot Centroid Estimation and Calibration Technologies for the Super-high Accuracy Star Tracker

TL;DR

This paper studies error sources and calibration techniques for super-high accuracy star trackers, proposing methods to improve pointing precision to better than 1 arcsecond for advanced scientific missions.

Contribution

It introduces novel algorithms and formulas, including CRLB constraint method and improved QUEST algorithm, to enhance star tracker accuracy and dynamic performance.

Findings

Achieved 10-20% improvement in attitude measurement accuracy.

Developed CRLB-based error budgeting for in-flight parameter optimization.

Enhanced QUEST algorithm for better star-based attitude determination.

Abstract

A pointing accuracy better than 1"(3sigma) star tracker plays a significant role for the advanced scientific missions. This thesis makes a series of studies on the typical error sources associated with the positioning and calibration processes, such as the centroiding algorithm, detector noise, motion, focal length drift, variation of the center wavelength of stellar spectrum, the model error, etc., some works of which are listed as follows: IWCOG algorithm is studied for the characteristics of both the accuracy and efficiency. Using Cramer-Rao Lower Bound theorem,centified to have an approximate optimum property for signal with Possion noise and the optimum feature in case of Gaussian noise. In order to enhance the dynamic performance, the generallized dynamic compensation formula is derived to compensate out the error from motion. decoupling of three technical indicators including dynamic performance, pointing accuracy and attitude output rate. To solve the problems exhibited in the in-orbit correction procedure, a brilliant idea, known as the CRLB constraint method, is presented to minimize some small error sources. To fulfill this goal, the full CRLB constaint formulas are derived to build a budget to limit the in-flight parameters. Using this method the overall error are obtained, which in turn results in three significant inferences. The attitude determination process is further optimized, by giving different weights to each star according to their magnitudes and the position over different star field, the QUEST algorithm is thus upgraded. The results show that this method can improve the attitude measurement accuracy statistically by 10-20%. The theory and deductions can be directly applied to various types of star trackers, whether it is a super-high accuracy one, or a high dynamic one.