天体测量信号的统计最佳拟合
Statistically optimal fitting of astrometric signals
摘要：
建立在极大似然框架基础上，开发了一维天体测量信号的通用拟合模型，并通过对一组真实图像实例的仿真来评估其性能。拟合质量分析作为用于信号扩展的术语的数量的函数，和天体测量误差，而不是相对于输入信号的RMS差异。调谐的功能基础的统计特性的信号合奏进行了讨论。拟合灵敏度的源光谱的先验知识的解决。目前的校准和数据减少方面的结果的一些影响进行了讨论，特别是相对于盖亚。
英文摘要：
A general purpose fitting model for one-dimensional astrometric signals is developed, building on a maximum likelihood framework, and its performance is evaluated by simulation over a set of realistic image instances. The fit quality is analysed as a function of the number of terms used for signal expansion, and of astrometric error, rather than RMS discrepancy with respect to the input signal. The tuning of the function basis to the statistical characteristics of the signal ensemble is discussed. The fit sensitivity to a priori knowledge of the source spectra is addressed. Some implications of the current results on calibration and data reduction aspects are discussed, in particular with respect to Gaia.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
