Star spot location estimation using Kalman filter for star tracker.

Star pattern recognition and attitude determination accuracy is highly dependent on star spot location accuracy for the star tracker. A star spot location estimation approach with the Kalman filter for a star tracker has been proposed, which consists of three steps. In the proposed approach, the approximate locations of the star spots in successive frames are predicted first; then the measurement star spot locations are achieved by defining a series of small windows around each predictive star spot location. Finally, the star spot locations are updated by the designed Kalman filter. To confirm the proposed star spot location estimation approach, the simulations based on the orbit data of the CHAMP satellite and the real guide star catalog are performed. The simulation results indicate that the proposed approach can filter out noises from the measurements remarkably if the sampling frequency is sufficient.

[1]  J. Crassidis.  Angular Velocity Determination Directly from Star Tracker Measurements , 2002 .

[2]  E. Dereniak,et al.  Gaussian profile estimation in one dimension. , 2007, Applied optics.

[3]  Carl Christian Liebe,et al.  Accuracy performance of star trackers - a tutorial , 2002 .

[4]  S. B. Grossman,et al.  Performance Analysis And Size Optimization Of Focal Planes For Point-Source Tracking Algorithm Applications , 1984 .

[5]  Shinhak Lee.  Pointing accuracy improvement using model-based noise reduction method , 2002, SPIE LASE.

[6]  Guo Ming.  Image Simulation of Star Sensor and Movement Characteristic Analysis of Background and Target , 2009 .

[7]  Hui Jia,et al.  Autonomous on-orbit calibration of a star tracker camera , 2011 .

[8]  Hui Jia,et al.  Novel approach for laboratory calibration of star tracker , 2010 .

[9]  Wang Changhong.  A predictive centroiding algorithm of unmatched stars for star sensor , 2009 .

[10]  Richard Hornsey,et al.  Determining star-image location: A new sub-pixel interpolation technique to process image centroids , 2007, Comput. Phys. Commun..

[11]  Ronald A. Downes,et al.  STIS target acquisition , 1997 .

[12]  Domenico Accardo,et al.  Enhancement of the centroiding algorithm for star tracker measure refinement , 2003 .

[13]  Jorge Ares,et al.  Influence of thresholding on centroid statistics: full analytical description. , 2004, Applied optics.

[14]  C. Liebe.  Star trackers for attitude determination , 1995 .

[15]  Rob Roy,et al.  Chirp Waveform Generation Using Digital Samples , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[16]  Noah Harold Smith.  Localized distortion estimation and correction for the ICESat star trackers , 2006 .

[17]  Daniele Mortari,et al.  StarNav III: a three fields of view star tracker , 2002, Proceedings, IEEE Aerospace Conference.

[18]  John L. Junkins,et al.  Predictive centroiding for star trackers with the effect of image smear , 2002 .

[19]  Jian Liu,et al.  Facet-based star acquisition method , 2004 .

[20]  Tao Zhang,et al.  A New Sub-Pixel Subdivision Location Algorithm for Star Image , 2009, 2009 2nd International Congress on Image and Signal Processing.

[21]  Yu Shi,et al.  Kalman-filtering-based angular velocity estimation using infrared attitude information of spacecraft , 2000 .

[22]  D. Mortari,et al.  Recursive mode star identification algorithms , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[23]  John L. Junkins,et al.  Attitude and interlock angle estimation using split-field-of-view star tracker , 2007 .

[24]  J. Keat.  Analysis of Least-Squares Attitude Determination Routine DOAO , 1977 .

[25]  I. Bar-Itzhack,et al.  Attitude Determination from Vector Observations: Quaternion Estimation , 1985, IEEE Transactions on Aerospace and Electronic Systems.