摘要
在CCD星敏感器中,快速而可靠的星图识别算法成为星敏感器确定姿态的最关键部分。针对星图识别中误匹配点的存在,提出了一种新的剔除误匹配点的方法—累积偏差法,选取合适的判定阈值对实验数据进行筛选,并结合最小二乘曲面拟合法对实验数据进行误差分析,实验结果表明,采用此方法,可以很好地剔除星图识别中的误匹配点,在赤经(α)和赤纬(δ)方向拟合偏差平均值可达到5.267 2,″星图正确匹配概率大大提高。
For star sensors in CCD, a fast and reliable star map identification algorithm is the most critical part for determining star sensor attitude. Since mismatching is existed in star map identification, a new method, cumulative departure method, was proposed to eliminate the mismatching points. The appropriate value was selected to filtrate the experimental data, and the error of the experiment data was analyzed with the least square surface fitting method. The experimental results showed that the mistaken matching points of the star map can be removed effectively by using this method; the average fitting error is 5. 267 2″ in the direction of α and δ, and the correct matching probability of star map is greatly improved.
出处
《电光与控制》
北大核心
2009年第9期40-43,共4页
Electronics Optics & Control
基金
国家自然科学基金(60532070)
关键词
星敏感器
星图识别
曲面拟合
误差分析
star sensors
star map recognition
surface fitting
error analysis
