A fast star image extraction algorithm for autonomous star sensors

Star sensors have been developed to acquire accurate orientation information in recent decades superior to other attitude measuring instruments. A star camera takes photos of the night sky to obtain star maps. An important step to acquire attitude knowledge is to compare the features of the observed stars in the maps with those of the cataloged stars using star identification algorithms. To calculate centroids of the star images before this step, they are required to be extracted from the star maps in advance. However, some large or ultra large imaging detectors are applied to acquire star maps for star sensors with the development of electronic imaging devices. Therefore, star image extraction occupies more and more portions of the whole attitude measurement period of time. It is required to shorten star image extraction time in order to achieve higher response rate. In this paper, a novel star image extraction algorithm is proposed which fulfill the tasks efficiently. By scanning star map, the pixels brighter than the gray threshold are found and their coordinates and brightness are stored in a cross-linked list. Data of these pixels are linked by pointers, while other pixels are neglected. Therefore, region growing algorithm can be used by choosing the first element in the list as a starting seed. New seeds are founded if the neighboring pixels are brighter than the threshold, and the last seed is deleted from the list. Next search continues until no neighboring pixels are in the list. At that time, one star image is extracted, and its centroid is calculated. Likely, other star images may be extracted, and then the examined seeds are deleted which are never considered again. A new star image search always begins from the first element for avoiding unnecessary scanning. The experiments have proved that for a 1024×1024 star map, the image extraction takes nearly 16 milliseconds. When CMOS APS is utilized to transfer image data, the real-time extraction can be almost achieved.

[1]  Byung-Hoon Lee,et al.  High-Accuracy Image Centroiding Algorithm for CMOS-Based Digital Sun Sensors , 2007 .

[2]  LI Chun-yan Centroiding algorithm for high-accuracy star tracker , 2006 .

[3]  Zhang Yulin Algorithm for CCD Star Image Rapid Locating , 2006 .

[4]  C. Liebe,et al.  The advancing state-of-the-art in second generation star trackers , 1998, 1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339).

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

[6]  Tian Jin-wen New star acquisition algorithm and optimization , 2005 .

[7]  M. Betto,et al.  The Bering autonomous target detection , 2003, International Conference on Recent Advances in Space Technologies, 2003. RAST '03. Proceedings of.

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

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

[10]  Carl Christian Liebe,et al.  New generation of autonomous star trackers , 1997, Remote Sensing.

[11]  Deng Nian-mao,et al.  Subdivided Locating Method of Single Star Image for Star Sensor , 2006 .

[12]  韩崇昭,et al.  A modified region growing algorithm for multi-colored image object segmentation , 2007 .

[13]  Peifa Jia,et al.  A survey of all-sky autonomous star identification algorithms , 2006, 2006 1st International Symposium on Systems and Control in Aerospace and Astronautics.

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

[15]  Liu Guangze,et al.  Research of subpixel subdivision location algorithm for star image based on biorthogonal wavelet , 2005 .

[16]  Ronald W. Armstrong,et al.  A survey of current solid state star tracker technology , 1985 .

[17]  Mie Sato,et al.  A gradient magnitude based region growing algorithm for accurate segmentation , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).