摘要
为解决巡天相机稳像控制精跟踪级系统高精度的光闭环问题,提出一种基于非下采样Contourlet变换(NSCT)去噪预处理和映射最小二乘支持向量机(MLSSVM)回归校正的星点定位方法。针对星图特点,采用自适应的基于NSCT的去噪方法来减小随机误差。从频域角度分析平方质心法系统误差产生的机理,得到其近似解析表达式;利用蒙特卡罗数值仿真的方法,用带有高斯径向基函数(RBF)核的映射MISSVM进行回归分析,得到星点质心的理想位置和系统误差的非线性函数关系,并用它进行系统误差的校正。仿真实验结果表明,提出的方法抗噪能力更强,星点定位精度提高1～2个数量级,具有更为优越的星点定位性能。
In order to resolve the problem of light closed loop for the level of fine tracking system of survey camera high-precision image stabilization control, a star location method is proposed based on nonsubsampled contourlet transform （NSCT） and mapped least squares support vector machine （MLSSVM）. Aiming at the characteristics of the star image, the image is denoised by adaptive NSCT. By analyzing the systematic errors of square centroid method in the frequency domain, its approximate analytic expression is obtained. By using Monte-Carlo numerical simulation method, regression analysis based on MLSSVM with radial basis function （RBF） kernel is proposed. The nonlinear function between the ideal star centroid location and the systematic errors is obtained, and is used to correct the systematic errors. Simulation results show that the proposed method is stronger in anti-noise performance and the star location accuracy is improved by 1 to 2 order of magnetude.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2013年第5期113-122,共10页
Acta Optica Sinica
基金
吉林省科技发展计划项目基金(20090311)
中国科学院领域前沿创新项目基金(201204)资助课题
