Nonlinear Kalman filters for calibration in radio interferometry
Nonlinear Kalman filters for calibration in radio interferometry
复制标题
用于无线电干涉测量校准的非线性卡尔曼滤波器
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
C. Tasse
中科院分区：
文献类型：
--
作者：
C. Tasse
新一代干涉仪产生的数据受到各种各样部分未知的复杂效应的影响，例如指向误差、相控阵波束、电离层、对流层、法拉第旋转或时钟漂移。大多数解决方向相关校准的算法求解有效的琼斯矩阵，并且不能约束无线电干涉测量方程（RIME）的基本物理量。一个相关的困难是，他们缺乏鲁棒性的存在下，低的信号tonoise比，当解决中等到大量的参数，他们可能会受到病态。这些效应可能在像平面中产生显著的后果，例如源噪声或甚至热噪声抑制。求解器直接估计RIME中出现的物理项的优点在于，它们可以潜在地将自由参数的数量减少数量级，同时显著增加可用数据的大小，从而改善条件。在这里，我们提出了一个新的校准方案的基础上的非线性版本的卡尔曼滤波器，其目的是估计出现在RIME的物理项。我们丰富了过滤器的结构与可调的数据表示模型，以及增强测量模型的正则化。使用模拟，我们表明，它可以正确地估计出现在RIME的物理效应。我们发现，这种方法是特别有用的，在最极端的情况下，如电离层和时钟效应同时存在。结合的能力，提供先验知识的预期结构的物理仪器的影响（预期的物理状态和动态），我们得到一个相当计算便宜的算法，我们认为是强大的，特别是在低信噪比制度。潜在地，使用滤波器和其他类似的方法可以代表在无线电干涉测量中的校准的改进，在破坏vibration的影响被理解和分析稳定的条件下。递归算法特别适用于预校准和流式方式的天空模型估计。这可能对SKA型仪器有用，因为它们产生大量数据，在取平均值之前必须进行校准。
The data produced by the new generation of interferometers are affected by a wide variety of partially unknown complex effects such as pointing errors, phased array beams, ionosphere, troposphere, Faraday rotation, or clock drifts. Most algorithms addressing direction-dependent calibration solve for the effective Jones matrices, and cannot constrain the underlying physical quantities of the radio interferometry measurement equation (RIME). A related difficulty is that they lack robustness in the presence of low signal-tonoise ratios, and when solving for moderate to large numbers of parameters they can be subject to ill-conditioning. These effects can have dramatic consequences in the image plane such as source or even thermal noise suppression. The advantage of solvers directly estimating the physical terms appearing in the RIME is that they can potentially reduce the number of free parameters by orders of magnitudes while dramatically increasing the size of usable data, thereby improving conditioning. We present here a new calibration scheme based on a nonlinear version of the Kalman filter that aims at estimating the physical terms appearing in the RIME. We enrich the filter’s structure with a tunable data representation model, together with an augmented measurement model for regularization. Using simulations we show that it can properly estimate the physical effects appearing in the RIME. We found that this approach is particularly useful in the most extreme cases such as when ionospheric and clock effects are simultaneously present. Combined with the ability to provide prior knowledge on the expected structure of the physical instrumental effects (expected physical state and dynamics), we obtain a fairly computationally cheap algorithm that we believe to be robust, especially in low signal-to-noise regimes. Potentially, the use of filters and other similar methods can represent an improvement for calibration in radio interferometry, under the condition that the effects corrupting visibilities are understood and analytically stable. Recursive algorithms are particularly well adapted for pre-calibration and sky model estimate in a streaming way. This may be useful for the SKA-type instruments that produce huge amounts of data that have to be calibrated before being averaged.