Star Tracker Based Attitude Determination Method For Spacecraft

Basically, a star tracker is an electronic camera connected to a microcomputer. The orientation of the spacecraft can be determined by star light vector. The attitude determination algorithms for APS(Active Pixel Sensor) star tracker were investigated. This paper includes two parts: the performance analysis of APS for star tracker and the algorithm of attitude determination, the latter is the central content. Some key problems were considered in the field of spacecraft attitude control. Such as: how to select the guide stars, how to realize star recognition quickly and robustly, how to determine attitude without prior attitude information, how to acquire attitude and attitude rate of spacecraft without gyro. The main work is as following: The detection sensitivity of APS star tracker is analyzed. A simple calculation approach of stellar detection limit for APS star tracker is provided. The sub-pixel Centeroiding of APS is investigated. Based on the model of star point and error calculating mode, the biases of sub-pixel centroiding due to the size of window, the variance of spot and the noise of APS are analyzed theoretically. The selection algorithm for guide stars was studied in detail. The star catalog and the distribution of stellar in celestial sphere are analyzed. The disadvantage of magnitude filtering method was pointed out; a new Boltzmann entropy based guide star selection algorithm was put forward. The guide stars selected by this algorithm satisfy the demand of star recognition and attitude determination at the same time. The SPR(Star Pattern Recognition)features such as angular distance visual magnitude and configuration of star group were investigated. A star pattern identification algorithm, based on angular distance and geometry configuration of star group, was provided in order to increase the probability of star pattern identification. A new searching algorithm, based on the probability of angular distance distribution, was provided and the result of experiment was given with specific parameters. A triangle star identification algorithm independent of star brightness was developed. The influences of matching threshold, centroiding errors to identification algorithm were analyzed. The validity and feasibility of this algorithm were proved by actual star image and emulational star image. It was proved that Boltzmann entropy is invariant with respect to coordinate transformation and robust under uncertainty. A new Boltzmann entropy based star identification algorithm was put forward in order to increase the robust of star identification. The singular values of star pattern vector matrix were utilized as identification feature in star pattern matching, and the minimum Boltzmann entropy was used as criteria to select star group. The nonlinear predictive filter method with the MME(Minimum Model Error) criteria was investigated in the condition of gyroless. The single vector measure and mult-vector measure were analyzed respectively based on the attitude kinematics and dynamics equation. During some special period, star tracker cannot work normally. An attitude prediction method was investigated, which used the AR predictive model. The one-step prediction and mult-step prediction were tested based on the kinamic equation and the wheel angular momentum.