Kalman Filtering in Radio Aperture Synthesis

这项研究的第一个目标是改进射电天文学 扩展源图像的大气卡尔曼滤波 在空间频率域中引起相位波动。 每个天线对的大气相位噪声模型为 通过时间序列分析得出。 射电源的模型 通过将CLEAN组件转换为 空间频率域，将它们置于同一时间基线 顺序作为数据，并对这些序列进行建模。 两款车型均 放入卡尔曼滤波器，然后将数据 过滤。 卡尔曼滤波器将区分想要的 和不需要的信号，从而产生较少损坏的数据集 这是准备映射。 第二个目标是通过以下方式减少图像中的噪声： 将图像分割成统计上稳定的片段， 对分段中的信号和噪声进行建模，以及卡尔曼滤波器， 过滤每一段。 这一领域的新工作将是 改进信息的合并;信号和噪声 在过滤器模式下进行处理。 一个例子是， 有色噪音 这将减少背景噪音， 降低天文信号中弱信号部分的噪声 object.

The first objective of this research is to improve radio astronomy images of extended sources by Kalman filtering the atmospherically induced phase fluctuations in the spatial frequency domain. Models for the atmospheric-phase noise for each antenna pair are obtained with times series analysis. A model for the radio source is obtained from the CLEAN components by transforming them to the spatial frequency domain, putting them in the same time-baseline order as the data, and modeling these series. Both models are placed in the Kalman filter and then the data are subsequently filtered. The Kalman filter will discriminate between the wanted and unwanted signals, thereby producing a less corrupted data set which is ready for mapping. The second objective is to reduce the noise in the images by segmenting the image into statistically stationary segments, modeling the signal and the noise in the segments, and Kalman filtering each segment. New work in this area will be the incorporation of improved information; the signal and noise processes in the filter modes. One example is the inclusion of colored noise. This will reduce the background noise and will reduce the noise in the weak-signal portion of the astronomical object.