A Quick Stable Approach Of Star Identification And Method For Adjusting The Single Star Simulator

The approach of star identification and the method for adjusting of single star simulator is discussed.The first section is about the approach of star identification.Star identification is the most critical and important process for attitude estimation. The main purpose of the star identification process is to identify the observed stars with the corresponding cataloged stars. The precision of traditional star identification method highly depend on the calibrated accuracy of the star camera parameters, mainly the focal length f, and the optical axis offsets. When parameters of the camera are not accurate or when the camera is not well calibrated, the proposed star identification method becomes very suitable, because it does not require accurate knowledge of these parameters. Monte Carlo experiment shows that the probability of failing Star-ID is less than 6.63%. The adoption of the k-vector range search technique, makes this method very fast, the speed of this star identification method is less than 30ms.The second section is about the method for adjusting of single star simulator.Star simulator is necessary equipment for calibration and performance testing of star sensor in laboratory. A novel method for adjustment of star simulator has been proposed in this paper. This method is based on ordinary Penta prism, guide rail, Charge Coupled Devices (CCD) camera and sub-pixel centroid algorithm. The CCD camera is used to image the star light replicated by the Penta prism instead of the autocollimator compared with the traditional adjustment of collimator. The analysis shows that the limiting parallelism error of the single star simulator is less than 0.49″; the experiment shows that the error is less than 2.32″after adjustment using this proposed method. The difference between analysis and experiment is attributed to diffraction limit of the collimator. It can satisfy the high accuracy adjustment of single star simulator. Furthermore, with the software of MATLAB and LABVIEW, this method can work automatically.