Satellite attitude determination utilizing measurement sensor data and kalman filtering

In this paper we present a method for attitude determination using star tracker sensor measurements and Kalman filter. A contingency attitude determination mode is required in the event of a primary sensor failure. Presented here are the sensor modeling and Kalman filtering portions of the Attitude Determination System (ADS) study. The paper is conducted with the purpose of evaluating the performance of a satellite ADS design. The measurement sensors are central and primary to the attitude pointing capability. We study in this paper a satellite equipped with both star sensors and rate measuring gyroscopes to perform the attitude determination. This assessment was done by using Monte Carlo methods to simulate these sensors. Using only star measurements an optimal satellite orientation estimate is found using the method of least squares, and the particular algorithm invoked is referred to ESOQ2 method. A successful Kalman filter algorithm for autonomous attitude determination is developed herein. This algorithm utilizes the three axis rate gyros for the satellite angular rate data and star camera line-of-sight measurements