Wang, T. 2009 一个使SVOM上仪器更快反应的方法
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| Title: | A Fast Onboard Star-Extraction Algorithm Optimized for the SVOM Visible Telescope | |
| Authors: | Wang, T.; Qiu, Y.; Cai, H.; Deng, J. | |
| Publication: | eprint arXiv:0907.1330 | |
| Publication Date: | 07/2009 | |
| Origin: | ARXIV | |
| Keywords: | Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena | |
| Comment: | 5 pages, PDF only, accepted for publication in Science in China Series G | |
| Bibliographic Code: | 2009arXiv0907.1330W |
Abstract
The Space multi-band Variable Object Monitor (SVOM) is a proposed Chinese astronomical satellite, dedicated to the detection, localization and measurement of the gamma-ray bursts (GRBs) on the cosmological scale. An efficient algorithm is developed for the purpose of onboard star extraction from the CCD images obtained with the Visible Telescope (VT) on board SVOM. The CCD pixel coordinates of the reference stars will be used to refine the astronomical position of the satellite, which will facilitate trigger rapid ground-based follow-up obsevations of the GRBs. In this algorithm, the image is divided into a number of grid cells and the "global" pixel-value maximum within each cell is taken as the first-guess position of a "bright" star. The correct center postion of a star is then computed using a simple iterative method. Applying two additional strategies, i.e., scanning the image only by even (or odd) lines or in a black-white chess board mode, are proposed to further reduce the time to extract the stars. To examine the efficiency of the above aglorithms, we applied them to the experimental images obtained with a ground-based telescope. We find that the accuracy of the astronomical positioning achieved by our method is comparable to that derived by using the conventional star-extraction method, while the former needs CPU time about 25 times less than the latter. This will significantly improve the performance of the SVOM VT mission.Bibtex entry for this abstract Preferred format for this abstract (see Preferences)

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