Citation: | Song Zhiming, Liu Guangqian, Qu Zhongquan. The auto guiding system combined with sub-pixel real-time gray projection algorithm[J]. Opto-Electronic Engineering, 2018, 45(8): 170586. doi: 10.12086/oee.2018.170586 |
[1] | Mandrini C H, Schmieder B, Démoulin P, et al. Topological analysis of emerging bipole clusters producing violent solar events[J]. Solar Physics, 2014, 289(6): 2041-2071. doi: 10.1007/s11207-013-0458-6 |
[2] |
邓林华. 一米红外太阳望远镜光电导行系统的研究[D]. 昆明: 中国科学院研究生院云南天文台, 2009.
Deng L H. Study on the auto guide unit system of one-meter infrared solar telescope in yunnan observatory[D]. Kunming: Yunnan Observatories, Chinese Academy of Sciences, 2009. |
[3] | 郭晶晶, 杨云飞, 冯松, 等.太阳望远镜高精度导行方法[J].科学通报, 2016, 61(10): 1112-1120. Guo J J, Yang Y F, Feng S, et al. High precision guide method for the solar telescope[J]. Chinese Science Bulletin, 2015, 61(10): 1112-1120. |
[4] | 柳光乾. 一米红外太阳望远镜控制系统研制[D]. 昆明: 中国科学院研究生院云南天文台, 2011. Liu G Q. Research and realization on control system of one meter infrared solar teleseope[D]. Kunming: Yunnan Observatories, Chinese Academy of Sciences, 2011. |
[5] | 柳光乾, 杨磊, 邓林华, 等.大气湍流对天文望远镜光电导行精度的影响[J].光学学报, 2013, 33(1): 7-11. Liu G Q, Yang L, Deng L H, et al. Influence of atmospheric turbulence on the accuracy of astronomical telescope auto-guiding system[J]. Acta Optica Sinica, 2013, 33(1): 7-11. |
[6] | 柳光乾, 程向明, 宋腾飞, 等.一米太阳望远镜风载对伺服系统的影响及控制[J].光电工程, 2011, 38(6): 50-58. doi: 10.3969/j.issn.1003-501X.2011.06.009 Liu G Q, Cheng X M, Song T F, et al. The influence and control of wind loading on the one meter solar telescope servosystem[J]. Opto-Electronic Engineering, 2011, 38(6): 50-58. doi: 10.3969/j.issn.1003-501X.2011.06.009 |
[7] | 李玉艳, 柳光乾.摆镜图像稳定控制系统在NVST中的应用研究[J].天文研究与技术, 2016, 13(1): 82-92. Li Y Y, Liu G Q. The study on the application of the stabilized control system for the tip-tilt mirror image in NVST[J]. Astronomical Research & Technology, 2016, 13(1): 82-92. |
[8] | Close L M, McCarthy D W. High resolution imaging with a tip-tilt Cassegrain secondary[J]. Publications of the Astronomical Society of the Pacific, 1994, 106(695): 77-86. |
[9] | Didkovsky L V, Dolgushyn A, Marquette W, et al. High-order adaptive optical system for big bear solar observatory[J]. Proceedings of SPIE, 2003, 4853: 630-639. doi: 10.1117/12.471341 |
[10] | 敦广涛, 屈中权.光纤阵列太阳光学望远镜偏振分析器设计[J].天文学报, 2012, 53(4): 342-352. Dun G T, Qu Z Q. Design of the polarimeter for the fibre arrayed solar optical telescope[J]. Acta Astronomica Sinica, 2012, 53(4): 342-352. |
[11] | Qu Z Q. A fiber arrayed solar optical telescope (FASOT)[C]//Proceedings of 6th Solar Polarization Workshop, 2011, 437: 423. |
[12] | 李长松, 姜爱民.空间太阳望远镜相关计算的FPGA实现技术[J].宇航学报, 2008, 29(4): 1350-1357. Li C S, Jiang A M. The realization of sst's correlation calculation based on FPGA[J]. Journal of Astronautics, 2008, 28(4): 1350-1357. |
[13] |
汪小勇. 基于灰度投影的实时电子稳像算法研究[D]. 杭州: 浙江大学, 2006.
Wang X Y. The research of real-time electronic image stabilization algorithm based on gray projection[D]. Hangzhou: Zhejiang University, 2006. |
[14] | 张艳超, 王芳, 赵建, 等.投影特征峰匹配的快速电子稳像[J].光学精密工程, 2015, 23(6): 1768-1773. Zhang Y C, Wang F, Zhao J, et al. Fast digital image stabilization based on characteristic peak of projection matching[J]. Optics and Precision Engineering, 2015, 23(6): 1768-1773. |
[15] | 孙辉.快速灰度投影算法及其在电子稳像中的应用[J].光学精密工程, 2007, 15(3): 412-416. Sun H. Fast gray projection algorithm and its application to electronic image stabilization[J]. Optics and Precision Engineering, 2007, 15(3): 412-416. |
[16] | 张永祥, 赵晓旭, 张伟功, 等.一种基于灰度投影的电子稳像改进算法[J].微电子学与计算机, 2008, 25(11): 212-215. Zhang Y X, Zhao X X, Zhang W G, et al. An improved electronic image stabilization algorithm based on gray projection algorithm[J]. Microelectronics & Computer, 2008, 25(11): 212-215. |
[17] | 李博, 王孝通, 杨常青, 等.电子稳像的灰度投影三点局域自适应搜索算法[J].光电工程, 2004, 31(9): 69-72. doi: 10.3969/j.issn.1003-501X.2004.09.018 Li B, Wang X T, Yang C Q, et al. Three-point locally adaptive searching in gray scale projection algorithm for electronic image stabilization[J]. Opto-electronic Engineering, 2004, 31(9): 69-72. doi: 10.3969/j.issn.1003-501X.2004.09.018 |
[18] | 孙辉, 张永祥, 熊经武, 等.高分辨率灰度投影算法及其在电子稳像中的应用[J].光学技术, 2006, 32(3): 378-380. Sun H, Zhang Y X, Xiong J W, et al. The application of high resolution gray projection algorithm in electronic image stabilization technology[J]. Optical Technique, 2006, 32(3): 378-380. |
Overview: Guiding systems serving modern astronomical telescopes are usually subjected to atmospheric and wind-borne disturbances that result in inaccurate calculation of the center of gravity of the guiding beacon. In order to solve this problem effectively, the sub-pixel real-time gray projection algorithm is nested into the algorithm of center of gravity of auto guiding system, which reduces the jitter of the center of gravity in a closed-loop cycle of auto guiding system without losing time resolution and achieves the goal of improving the performance of auto guiding system. First of all, in the paper, we indicate that the atmospheric turbulence and wind are two things that have a bad influence on the performance of auto guiding system, and then describe some existing methods used to suppress the two things. Afterwards, we have a knowledge about that to suppress the influence of the atmospheric turbulence, in a closed-loop cycle of auto guiding system, the time of calculating guiding beacon's center of gravity is significant, and to suppress the influence of wind, reducing the error of guiding beacon's center of gravity is indispensable. Therefore, we propose an efficient method that takes advantages of gray projection algorithm to calculate the displacement vector between adjacent images of auto guiding system in the time when the guiding beacon's center of gravity is computed, and then compensates the displacement vector for the center of gravity so that the influences from atmospheric turbulence and wind are suppressed, simultaneously. On the other hand, we are aware of that the performance of our method mentioned above can be further improved through rectifying three aspects of our method in algorithm. One is that making use of the structural similarity between gray projection algorithm and the algorithm of guiding beacon's center of gravity, some combinations between the two algorithms can be conducted to speed up their execution. Two is that through comparing with existing searching algorithms of minimum value of correlation function, which are an important part of gray projection algorithm, an efficient searching algorithm named as three point searching is further improved in order to obtain a promotion of computational speed of gray projection algorithm. Three is that based on the characteristic of correlation function of gray projection algorithm, an efficient fitting method in possession of a sub-pixel accuracy is applied to the correlation function so that the gray projection algorithm can obtain a sub-pixel accuracy. Finally, some experiments are conducted, and corresponding results show that our method can efficiently improve the performance of auto guiding system.
The deviation of center of gravity of the auto guiding system. (a) Reference image and the centers of gravity of reference image and current image; (b) Current image and its center of gravity
The results of gray projection from Fig. 1. (a) The projections of XC(i) and XR(i); (b) The projections of YC(i) and YR(i)
Correlation function curves of horizontal and vertical direction. (a) The curve of RX(mp); (b) The curve of RY(mq)
The pseudo code embedded in the algorithm of center of gravity and gray projection algorithm
The schematic diagrams of the searching algorithm of correlation function. (a) The global searching algorithm; (b) The three point searching algorithm from center to both sides; (c) Algorithm in this paper
The auto guiding system used by our algorithm
The auto guiding system's jitter of the center of gravity in the random wind load. (a) The measured values of wind load in our experiment; (b) The relative jitter of the center of gravity in the x direction; (c) The relative jitter of the center of gravity in the y direction