空间太阳望远镜稳像系统中图像相关器的研究
摘要
空间太阳望远镜是我国自主研发的第一颗天文卫星。主要用于对太阳的全日制、多波段以及高分辨率观察。将有助于太阳小尺度磁场和活动区磁场精细结构的研究,并有望取得突破性进展,因此曾被国外媒体称为“雄心勃勃的大计划”。
空间太阳望远镜的1m主光学系统具有0.1″的瑞利衍射极限分辨率。望远镜本身的卫星平台仅能提供±6″的指向精度和3″/s的姿态稳定度,由于卫星本身的震动以及太阳自转会造成积分时间内的成像模糊。在必需增加积分时间以提高CCD图像信噪比的情况下,需要利用相关跟踪器改正,实现对成像的运动补偿。
本文对空间太阳望远镜相关跟踪器的目标图像特征进行了分析。考虑到太阳米粒组织的对比度比较低、形状不规则等特点,沿用了国内外一贯采用的相关算法实现图像偏移检测。相关算法在整像元偏移检测上具有很好的效果,辅助亚像元拟合可以得到更高的检测精度。本文通过对大量米粒图像进行仿真分析发现,引入修正参数后的曲面拟合算法可以进一步提高亚像元偏移检测精度。其中修正参数是利用统计学方法对其分布进行分析后,根据数学期望的估计值得到的。
对于整个相关跟踪系统来说,相关计算十分费时。过去由于器件水平有限,太阳望远镜的相关跟踪系统难以实现快速计算,造成了系统具有明显时滞特征。而纯时滞系统的闭环特性与时延有反比关系,因此寻求快速相关实现方法成为类似系统所需解决的关键之一。快速相关器的设计可以利用简化相关算法实现,主要是减少乘法的次数,例如以减法相关算法取代乘法相关算法。但是,减法相关算法容易产生零漂。本文在总结前人的经验基础上,根据当今集成电路发展的水平,采用了高集成度的FPGA实现相关运算。利用并行算法将相关运算进行分解,并与FPGA的结构特点相结合,设计出并行相关计算单元。使之具有模块化、数控分流等特点。充分利用了硬件资源,达到缩短计算时间的目的。
利用FPGA实现相关运算的数据结构为浮点格式。考虑到资源有限,在保证运算过程不发生溢出的情况下,采用18 bits的浮点运算。通过实际测试,相关矩阵的计算结果与双精度浮点的相比,相对误差在2‰～6‰之间。
利用理论推导、仿真波形和示波器测试都可以验证,整个相关计算时间约为240us。满足空间太阳望远镜的需求。
综上所述,拟合修正参数的引入改善了亚像元偏移检测精度,为高精度亚像元偏移检测提供了算法保证;利用并行算法和FPGA结构特点相结合的方法,极大缩短了相关运算的计算时间。实现了计算时间和计算精度指标的优化。本文的相关跟踪计算单元不但满足了相关跟踪器的指标需求,而且为其他类似实时高精度数据处理系统提供设计参考。
The Space Solar Telescope (SST), proposed by Chinese scientists independently, is described as "the ambitious big plan" by the overseas media. Its main objective is to study the sun using five payloads, which will be helpful in researching the small-scale solar magnetic field, and hope to achieve a breakthrough.
On the one hand, we need to increase the integration time to improve the signal to noise ratio (SNR) of the CCD image. On the other hand, the satellite platform of SST can only provide±6" pointing accuracy and 3"/s attitude stability. So the Main Optical Telescope (MOT) can not realize its 0.1" resolution without help. Under this circumstance, it is necessary to use a correlation tracker (CT) to stabilze the image.
In this paper, considering the low contrast and irregularity of solar granulation, we use the correlation algorithm to detect the image movement, which is widely adopted by both foreign and domestic scientists. The correlation algorithm can be calculated by three steps. Firstly, the integral offset between the reference image and the live image can be found by getting the coordinates of the peak of correlation matrix. Secondly, sub-pixel offset can be determined by fitting the 5 by 5 matrix around the peak of correlation matrix with a parabolic surface. Finally, the total offset can be calculated by adding the integral offset to sub-pixel offset. After a large number of simulation experiments, we find that adding two parameters, obtained by statistical method, at the final step can reduce the error in image offset detection.
It is a pure time delay system characteristic that its bandwidth is inverse proportion to the delay time. So, to realize the correlation algorithm as far as possible is one of the correlation tracker’s key tasks. By full utilizing the characteristics of FPGA, we realize the design of correlation tracker’s calculation unit and short the calculation time in great degree by modular design and pipeline organization.
The 18-bit floating-point data structure can not only satisfy the restriction of XCV800 FPGA resource, but also ensure no overflow occurs during the caluculation. Through many tests, the relative error of correlation matrix between the results of our design and MATLAB program is better than 6‰.
From theoretical analysis, simulated waveform, and oscilloscope’s measurement, we can draw the conclusion that the correlation calculation time of our design is about 240us, which is great shorter than other designs.
Above all, we improve the accuracy of image offset detection by using the modified fitting algorithm, and reduce the correlation calculation time by combining the parallel algorithm and the characteristics of FPGA. The solution we provided can not only meet the needs of correlation tracker, but also provide a reference to other similar applications.
空间太阳望远镜的1m主光学系统具有0.1″的瑞利衍射极限分辨率。望远镜本身的卫星平台仅能提供±6″的指向精度和3″/s的姿态稳定度,由于卫星本身的震动以及太阳自转会造成积分时间内的成像模糊。在必需增加积分时间以提高CCD图像信噪比的情况下,需要利用相关跟踪器改正,实现对成像的运动补偿。
本文对空间太阳望远镜相关跟踪器的目标图像特征进行了分析。考虑到太阳米粒组织的对比度比较低、形状不规则等特点,沿用了国内外一贯采用的相关算法实现图像偏移检测。相关算法在整像元偏移检测上具有很好的效果,辅助亚像元拟合可以得到更高的检测精度。本文通过对大量米粒图像进行仿真分析发现,引入修正参数后的曲面拟合算法可以进一步提高亚像元偏移检测精度。其中修正参数是利用统计学方法对其分布进行分析后,根据数学期望的估计值得到的。
对于整个相关跟踪系统来说,相关计算十分费时。过去由于器件水平有限,太阳望远镜的相关跟踪系统难以实现快速计算,造成了系统具有明显时滞特征。而纯时滞系统的闭环特性与时延有反比关系,因此寻求快速相关实现方法成为类似系统所需解决的关键之一。快速相关器的设计可以利用简化相关算法实现,主要是减少乘法的次数,例如以减法相关算法取代乘法相关算法。但是,减法相关算法容易产生零漂。本文在总结前人的经验基础上,根据当今集成电路发展的水平,采用了高集成度的FPGA实现相关运算。利用并行算法将相关运算进行分解,并与FPGA的结构特点相结合,设计出并行相关计算单元。使之具有模块化、数控分流等特点。充分利用了硬件资源,达到缩短计算时间的目的。
利用FPGA实现相关运算的数据结构为浮点格式。考虑到资源有限,在保证运算过程不发生溢出的情况下,采用18 bits的浮点运算。通过实际测试,相关矩阵的计算结果与双精度浮点的相比,相对误差在2‰～6‰之间。
利用理论推导、仿真波形和示波器测试都可以验证,整个相关计算时间约为240us。满足空间太阳望远镜的需求。
综上所述,拟合修正参数的引入改善了亚像元偏移检测精度,为高精度亚像元偏移检测提供了算法保证;利用并行算法和FPGA结构特点相结合的方法,极大缩短了相关运算的计算时间。实现了计算时间和计算精度指标的优化。本文的相关跟踪计算单元不但满足了相关跟踪器的指标需求,而且为其他类似实时高精度数据处理系统提供设计参考。
The Space Solar Telescope (SST), proposed by Chinese scientists independently, is described as "the ambitious big plan" by the overseas media. Its main objective is to study the sun using five payloads, which will be helpful in researching the small-scale solar magnetic field, and hope to achieve a breakthrough.
On the one hand, we need to increase the integration time to improve the signal to noise ratio (SNR) of the CCD image. On the other hand, the satellite platform of SST can only provide±6" pointing accuracy and 3"/s attitude stability. So the Main Optical Telescope (MOT) can not realize its 0.1" resolution without help. Under this circumstance, it is necessary to use a correlation tracker (CT) to stabilze the image.
In this paper, considering the low contrast and irregularity of solar granulation, we use the correlation algorithm to detect the image movement, which is widely adopted by both foreign and domestic scientists. The correlation algorithm can be calculated by three steps. Firstly, the integral offset between the reference image and the live image can be found by getting the coordinates of the peak of correlation matrix. Secondly, sub-pixel offset can be determined by fitting the 5 by 5 matrix around the peak of correlation matrix with a parabolic surface. Finally, the total offset can be calculated by adding the integral offset to sub-pixel offset. After a large number of simulation experiments, we find that adding two parameters, obtained by statistical method, at the final step can reduce the error in image offset detection.
It is a pure time delay system characteristic that its bandwidth is inverse proportion to the delay time. So, to realize the correlation algorithm as far as possible is one of the correlation tracker’s key tasks. By full utilizing the characteristics of FPGA, we realize the design of correlation tracker’s calculation unit and short the calculation time in great degree by modular design and pipeline organization.
The 18-bit floating-point data structure can not only satisfy the restriction of XCV800 FPGA resource, but also ensure no overflow occurs during the caluculation. Through many tests, the relative error of correlation matrix between the results of our design and MATLAB program is better than 6‰.
From theoretical analysis, simulated waveform, and oscilloscope’s measurement, we can draw the conclusion that the correlation calculation time of our design is about 240us, which is great shorter than other designs.
Above all, we improve the accuracy of image offset detection by using the modified fitting algorithm, and reduce the correlation calculation time by combining the parallel algorithm and the characteristics of FPGA. The solution we provided can not only meet the needs of correlation tracker, but also provide a reference to other similar applications.
引文
[1] 布朗, 施密特. 空间太阳望远镜评估研究报告[M]. 中国科学院北京天文台, 1997
[2] 艾国祥, 施密特. 空间太阳望远镜 A 相研究报告[M]. 中国科学院北京天文台, 1997
[3] ESA. http://www.esa.int/esaSC/index.html
[4] Toshifumi Shimizu, Shin’ich Nagata, Chris Edwards, et al. Image stabilization system on SOLOR-B Solar Optical Telescope [J]. Optical, Infrared, and Millimeter Space Telescopes (SPIE), 2004,5487: 1199-1206
[5] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 2007
[6] 王宇舟. 空间太阳望远镜 MOT 图像预处理技术与系统研究[D]. 中国科学院研究生院,2005
[7] Edwards,C.G.,Levay,M.,Gilbreth,C.W,et al. The correlation tracker image stabilization system for HRSO[J]. Bulletin of the American Astronomical Society. 1987,19:929.
[8] O.von der Lühe, A.L.Widener, Th. Rimmele, et al. Solar feature correlation tracker for ground-based telescopes[J]. Astron and Astrophys. 1989,224:351-360.
[9] E.Ballesteros, M.Collados, J.A.Bonet,et al. Two-dimensional, high spatial resolution, solar spectroscopy using a Correlation Tracker[J]. Astronomy & Astrophysics Supplement Series. 1996,115:353-365.
[10] G.Molodij, J.Rayrole, P.Y.Madec,et al. Performance analysis for T.H.E.M.I.S image stabilizer optical system[J]. Astronomy & Astrophysics Supplement Series. 1996,118:169-179.
[11] Leonid V. Didkovsky, Alexander I. Dolgushyn, et al. High-order adaptive optical system for Big Bear Solar Observatory[J]. Innovative Telescopes and Instrumentation for Solar Astrophysics (SPIE), 2003, 4853: 630-639.
[12] M.Shand,G.B.Scharmer,W.Wei. Correlation Tracking and Adaptive Optics Control Using Off-The-Shelf Workstation Technology[J]. High Resolution Solar Physics: Theory, Observations, and Technique ASP Conference Series, 1999, 183:231-238.
[13] Toshifumi Shimizu, Shin’ich Nagata, Chris Edwards, et al. Image stabilization system on SOLOR-B Solar Optical Telescope [J]. Optical, Infrared, and Millimeter Space Telescopes (SPIE), 2004,5487: 1199-1206.
[14] 徐秉铮, 欧阳景正. 信号分析与相关技术[M]. 科学出版社, 1981
[15] 蒋增荣, 曾泳泓, 余品能. 快速算法[M]. 国防科技大学出版社, 1993
[1] 艾国祥, 施密特. 空间太阳望远镜 A 相研究报告[M]. 中国科学院北京天文台, 1997
[2] Li,C.S, Jin S.Z. The Implement of High Speed Correlation Tracking Algorithm Based on FPGA in Space Solar Telescope[J], 8th International Conference on Signal Processing,2006,1:565-568.
[3] 王宇舟. 空间太阳望远镜 MOT 图像预处理技术与系统研究[D]. 中国科学院研究生院,2005
[4] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 中国科学院研究生院,2007
[5] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[6] O.von der Lühe, A.L.Widener, Th. Rimmele, et al. Solar feature correlation tracker for ground-based telescopes [J]. Astron and Astrophys. 1989,224:351-360.
[1] 王蕾. 图像配准技术及应用研究[D]. 西安电子科技大学, 2007
[2] 毛晓冬. 图像配准与拼接方法研究[D]. 西安电子科技大学, 2006
[3] 郑志彬, 叶中付. 基于相位相关的图像配准算法[J]. 数据采集与处理, 2006, 21:444-449
[4] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 中国科学院研究生院,2007
[5] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[6] 伯晓晨, 李涛, 刘路等. Matlab 工具箱应用指南[M]. 电子工业出版社, 2000
[7] 向敬成, 刘醒凡. 信号理论[M]. 成都电讯工程学院出版社,1988
[8] 徐秉铮, 欧阳景正. 信号分析与相关技术[M]. 科学出版社,1981
[9] 《数学手册》编写组. 数学手册[M]. 高等教育出版社,1979
[1] 曾泳泓, 成礼智, 周敏. 数字信号处理的并行算法[M]. 国防科技大学出版社, 1999
[2] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[3] 胡广书, 数字信号处理[M]. 清华大学出版社, 1997
[4] 蒋增荣, 曾泳泓, 余品能. 快速算法[M]. 国防科技大学出版社, 1993
[5] Xilinx. http://www.xilinx.com.
[6] 邢克飞, 杨俊, 王跃科 等. XilinxSRAM 型 FPGA 抗辐射设计技术研究[J]. 宇航学报. 2007, 28:123-151
[7] 王志华, 邓仰东. 数字集成系统的结构化设计与高层次综合[M]. 清华大学出版社,2000
[8] Texas Instruments. TMS320C3X User’s Guide.
[9] Nabeel Shirazi, Al Walters, Peter Athanas. Quantitative Analysis of Floating Point Arithmeticon FPGA Based Custom Computing Machines [J]. IEEE Symposium on FPGAs for Custom Computing Machines. 1995
[1] 任晓东, 文博. CPLD/FPGA 高级应用开发指南[M]. 电子工业出版社, 2003
[2] Xilinx. http://www.xilinx.com
[3] Jan M. Rabaey, Anantha Chandrakasan, Borivoje Nikolic. 数字集成电路[M]. 电子工业出版社, 2006
[4] Michael John, Sebastian Smith. 专用集成电路[M]. 电子工业出版社, 2005
[1] 应启珩, 冯一云, 窦维蓓. 离散时间信号分析和处理[M]. 清华大学出版社, 2001
[2] 耿立红, 孙才红, 李长松. 基于 FPGA 的空间太阳望远镜图像相关算法实现[J]. 电子学报. 2006,34:147-151
[3] Li,C.S, Jin S.Z. The Implement of High Speed Correlation Tracking Algorithm Based on FPGA in Space Solar Telescope[J], 8th International Conference on Signal Processing,2006,1:565-568
[2] 艾国祥, 施密特. 空间太阳望远镜 A 相研究报告[M]. 中国科学院北京天文台, 1997
[3] ESA. http://www.esa.int/esaSC/index.html
[4] Toshifumi Shimizu, Shin’ich Nagata, Chris Edwards, et al. Image stabilization system on SOLOR-B Solar Optical Telescope [J]. Optical, Infrared, and Millimeter Space Telescopes (SPIE), 2004,5487: 1199-1206
[5] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 2007
[6] 王宇舟. 空间太阳望远镜 MOT 图像预处理技术与系统研究[D]. 中国科学院研究生院,2005
[7] Edwards,C.G.,Levay,M.,Gilbreth,C.W,et al. The correlation tracker image stabilization system for HRSO[J]. Bulletin of the American Astronomical Society. 1987,19:929.
[8] O.von der Lühe, A.L.Widener, Th. Rimmele, et al. Solar feature correlation tracker for ground-based telescopes[J]. Astron and Astrophys. 1989,224:351-360.
[9] E.Ballesteros, M.Collados, J.A.Bonet,et al. Two-dimensional, high spatial resolution, solar spectroscopy using a Correlation Tracker[J]. Astronomy & Astrophysics Supplement Series. 1996,115:353-365.
[10] G.Molodij, J.Rayrole, P.Y.Madec,et al. Performance analysis for T.H.E.M.I.S image stabilizer optical system[J]. Astronomy & Astrophysics Supplement Series. 1996,118:169-179.
[11] Leonid V. Didkovsky, Alexander I. Dolgushyn, et al. High-order adaptive optical system for Big Bear Solar Observatory[J]. Innovative Telescopes and Instrumentation for Solar Astrophysics (SPIE), 2003, 4853: 630-639.
[12] M.Shand,G.B.Scharmer,W.Wei. Correlation Tracking and Adaptive Optics Control Using Off-The-Shelf Workstation Technology[J]. High Resolution Solar Physics: Theory, Observations, and Technique ASP Conference Series, 1999, 183:231-238.
[13] Toshifumi Shimizu, Shin’ich Nagata, Chris Edwards, et al. Image stabilization system on SOLOR-B Solar Optical Telescope [J]. Optical, Infrared, and Millimeter Space Telescopes (SPIE), 2004,5487: 1199-1206.
[14] 徐秉铮, 欧阳景正. 信号分析与相关技术[M]. 科学出版社, 1981
[15] 蒋增荣, 曾泳泓, 余品能. 快速算法[M]. 国防科技大学出版社, 1993
[1] 艾国祥, 施密特. 空间太阳望远镜 A 相研究报告[M]. 中国科学院北京天文台, 1997
[2] Li,C.S, Jin S.Z. The Implement of High Speed Correlation Tracking Algorithm Based on FPGA in Space Solar Telescope[J], 8th International Conference on Signal Processing,2006,1:565-568.
[3] 王宇舟. 空间太阳望远镜 MOT 图像预处理技术与系统研究[D]. 中国科学院研究生院,2005
[4] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 中国科学院研究生院,2007
[5] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[6] O.von der Lühe, A.L.Widener, Th. Rimmele, et al. Solar feature correlation tracker for ground-based telescopes [J]. Astron and Astrophys. 1989,224:351-360.
[1] 王蕾. 图像配准技术及应用研究[D]. 西安电子科技大学, 2007
[2] 毛晓冬. 图像配准与拼接方法研究[D]. 西安电子科技大学, 2006
[3] 郑志彬, 叶中付. 基于相位相关的图像配准算法[J]. 数据采集与处理, 2006, 21:444-449
[4] 姜钊, 空间太阳望远镜中 1-bit 图像相关器的研究[D]. 中国科学院研究生院,2007
[5] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[6] 伯晓晨, 李涛, 刘路等. Matlab 工具箱应用指南[M]. 电子工业出版社, 2000
[7] 向敬成, 刘醒凡. 信号理论[M]. 成都电讯工程学院出版社,1988
[8] 徐秉铮, 欧阳景正. 信号分析与相关技术[M]. 科学出版社,1981
[9] 《数学手册》编写组. 数学手册[M]. 高等教育出版社,1979
[1] 曾泳泓, 成礼智, 周敏. 数字信号处理的并行算法[M]. 国防科技大学出版社, 1999
[2] 香帕尼, 傅里叶变换及其物理应用[M]. 科学出版社, 1980
[3] 胡广书, 数字信号处理[M]. 清华大学出版社, 1997
[4] 蒋增荣, 曾泳泓, 余品能. 快速算法[M]. 国防科技大学出版社, 1993
[5] Xilinx. http://www.xilinx.com.
[6] 邢克飞, 杨俊, 王跃科 等. XilinxSRAM 型 FPGA 抗辐射设计技术研究[J]. 宇航学报. 2007, 28:123-151
[7] 王志华, 邓仰东. 数字集成系统的结构化设计与高层次综合[M]. 清华大学出版社,2000
[8] Texas Instruments. TMS320C3X User’s Guide.
[9] Nabeel Shirazi, Al Walters, Peter Athanas. Quantitative Analysis of Floating Point Arithmeticon FPGA Based Custom Computing Machines [J]. IEEE Symposium on FPGAs for Custom Computing Machines. 1995
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