大气湍流畸变波前斜率的稀疏分解
[1] 鲜浩. 自适应光学系统波前传感器设计与优化[D]. 成都: 电子科技大学, 2008.
Xian H. Design and optimization of wavefront sensor for adaptive optics system[D]. Chengdu: University of Electronic Science and Technology of China, 2008.
[2] 曹召良, 穆全全, 徐焕宇, 等. 开环液晶自适应光学系统: 研究进 展和结果(英文)[J]. 红外与激光工程, 2016, 45(4): 0402002.
[3] 陆长明, 饶长辉, 黄惠明, 等. 天文学自适应光学成像望远镜的 模拟[J]. 光电工程, 2006, 33(1): 20–23.
Lu C M, Rao C H, Huang H M, et al. Simulation of an astronomical adaptive optics imaging telescope[J]. Opto-Electronic Engineering, 2006, 33(1): 20–23.
[4] 蒋志凌. 哈特曼波前传感器特性和应用研究[D]. 武汉:武汉物理与数学研究所, 2005.
Jiang Z L. Study on characteristics and applications of Hartmann wavefront sensor[D]. Wuhan: Wuhan Institute of Physics and Mathematics of Chinese Academy of Sciences, 2005.
[5] Rostami M, Michailovich O, Wang Z. Image Deblurring using derivative compressed sensing for optical imaging application[ J]. IEEE Transactions on Image Processing, 2012, 21(7): 3139–3149.
[6] Polans J, Mcnabb R P, Izatt J A, et al. Compressed wavefront sensing[J]. Optics Letters, 2014, 39(5): 1189–1192.
[7] Candes E J, Romberg J, Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2): 489–509.
[8] 管蓉. 基于压缩感知的图像稀疏表示方法[D]. 太原: 中北大学, 2012.
Guan R. The sparse representation method based on compressed sensing[D]. Taiyuan: North University of China, 2012.
[9] 徐勇峻. 基于信号稀疏表示的字典设计[D]. 南京: 南京理工大学, 2013.
Xu Y J. Dictionary design based on sparse representation of signals[D]. Nanjing: Nanjing University of Science and Technology, 2013.
[10] 吕方旭, 张金成, 王泉, 等. 基于傅里叶基的自适应压缩感知重 构算法[J]. 北京航空航天大学学报, 2014, 40(4): 544–550.
Lv F X, Zhang J C, Wang Q, et al. Adaptive recovery algorithm for compressive sensing based on Fourier basis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(4): 544–550.
[11] 刘丹华. 信号稀疏分解及压缩感知理论应用研究[D]. 西安: 西安电子科技大学, 2009.
Liu D H. Research on sparse signal decomposition and compressed sensing theory[D]. Xi’an: Xidian University, 2009.
[12] 尹航, 宋新, 闫野. 星图的稀疏表示性能[J]. 光学 精密工程, 2015, 23(2): 573–581.
Yin H, Song X, Yan Y. Performance on sparse representation of star images[J]. Optics and Precision Engineering, 2015, 23(2): 573–581.
[13] 张智露. 室内大气湍流模拟系统的研究[D]. 太原: 太原理工大学, 2017.
Zhang Z L. Research on the simulation system of indoor atmospheric turbulence[D]. Taiyuan: Taiyuan University of Technology, 2017.
[14] 蔡冬梅, 王昆, 贾鹏, 等. 功率谱反演大气湍流随机相位屏采样 方法的研究[J]. 物理学报, 2014, 63(10): 104217.
Cai D M, Wang K, Jia P, et al. Sampling methods of power spectral density method simulating atmospheric turbulence phase screen[J]. Acta Physica Sinica, 2014, 63(10): 104217.
[15] Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655–4666.
[16] Jia P, Cai D M, Wang D, et al. Simulation of atmospheric turbulence phase screen for large telescope and optical interferometer[ J]. Monthly Notices of the Royal Astronomical Society, 2015, 447(4): 3467–3474.
[17] 王奇涛, 佟首峰, 徐友会. 采用Zernike 多项式对大气湍流相位 屏的仿真和验证[J]. 红外与激光工程, 2013, 42(7): 1907–1911.
Wang Q T, Tong S F, Xu Y H. On simulation and verification of the atmospheric turbulent phase screen with Zernike polynomials[ J]. Infrared and Laser Engineering, 2013, 42(7): 1907–1911.
[18] Zhang Q, Jiang W H, Xu B. Study of Zonal wavefront reconstruction adapting for Hartmann-Shack wavefront sensor[J]. High Power Laser and Particle Beams, 1998, 10(2): 229–233.
[19] Aharon M, Elad M, Bruckstein A. RMK-SVD: an algorithm for designing overcomplete dictionaries for sparse representation[ J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4311–4322.
李娟娟, 蔡冬梅, 贾鹏, 李灿. 大气湍流畸变波前斜率的稀疏分解[J]. 光电工程, 2018, 45(2): 170616. Li Juanjuan, Cai Dongmei, Jia Peng, Li Can. Sparse decomposition of atmospheric turbulence wavefront gradient[J]. Opto-Electronic Engineering, 2018, 45(2): 170616.