Optics and Precision Engineering, Volume. 27, Issue 11, 2467(2019)
Star identification algorithm based on similar triangle principle
The star identification algorithm is a key technology for star sensors. Traditional star identification algorithms, such as triangle algorithm, polygon algorithm, and other improved algorithms mainly consider the star diagonal distance as an identification feature. The accuracy of the calculated star diagonal distance is dependent on the calibration accuracy of the focus length of the charge-coupled device (CCD) camera. These identification algorithms cannot work properly if the calibration accuracy is insufficient or if the focus length of the camera changes significantly owing to environmental conditions. This paper proposed a new star identification algorithm based on the similar triangle, which operated using the similar triangles between the observed triangle and the triangle consisting of image points of the CCD camera. Because the identification process was not dependent on the focus length, it still had a large focus error. Finally, simulation verification was carried out with the Monte Carlo method. The results show that the recognition rate of the proposed algorithm remains unchanged, with large focus length error. The proposed algorithm has an average recognition rate of 95.2% while the recognition speed can reach 5.3 ms. In contrast, the average recognition speed of the traditional triangle algorithm is approximately 7.6 ms under the same experimental conditions. The proposed algorithm and traditional triangle algorithm has a recognition rate of 93.3% and 86.5%, respectively, when the image position error is 0.5 pixels. Compared with the traditional triangle algorithm, the proposed algorithm has higher speed and improved robustness.
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SU De-zhi, WANG Yu-liang, WU Shi-yong, CUI Xiao-dong. Star identification algorithm based on similar triangle principle[J]. Optics and Precision Engineering, 2019, 27(11): 2467
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Received: Feb. 28, 2019
Accepted: --
Published Online: Jan. 7, 2020
The Author Email: De-zhi SU (sudezhifun@163.com)