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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ming Jiang Yi-Zheng Ye Ming-Yan Yu Jin-Xiang Wang Bao-Hua Li |
| Copyright Year | 2007 |
| Description | Author affiliation: Harbin Inst. of Technol., Harbin (Ming Jiang; Yi-Zheng Ye; Ming-Yan Yu; Jin-Xiang Wang; Bao-Hua Li) |
| Abstract | Triangle algorithm is used widely in the field of star pattern recognition, but it also has disadvantage that recognition reliability decreases seriously in areas where there are many stars existing small angular separation. The character match algorithm can solve this problem and it has small size of guide star database, but it can not recognize a star image with displacement caused by camera movement and rotation. To overcome this disadvantage, an effective star pattern recognition algorithm is proposed in this paper. This algorithm divided the entire celestial sphere into a lot of square areas based on some bright stars during constructing guide star database, and then it used sub-areas selected from these square areas for star pattern recognition according to characteristic of star image sensed by star sensor. The simulation results show that the algorithm in this paper not only inherits advantages of character match algorithm, but also has strong robustness against star image displacement. |
| Starting Page | 2673 |
| Ending Page | 2677 |
| File Size | 536118 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424409723 |
| DOI | 10.1109/ICMLC.2007.4370601 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pattern recognition Image databases Pattern matching Position measurement Machine learning algorithms Character recognition Image recognition Space missions Space vehicles Machine learning Character match Star sensor Star pattern recognition |
| Content Type | Text |
| Resource Type | Article |
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