减少以26兆赫兹频率通过电离层的无线电波相位波动的状态空间方法

A. Okatan
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引用次数: 1

摘要

在这项工作中,射电天文学中最重要的问题之一受到了攻击。在射电天文学中,为了获得良好的角度分辨率,天线阵列使用了很长的基线。对于3000公里的基线,双单元阵列给出了一个抛物线天线的效果,如果它有3000公里的半径。由于天线之间的距离很大,天线可以看到电离层的不同部分。两根天线看到的这些不同区域具有不同的随机动态结构,这些动态时变结构的相关性很小。电离层两个不同区域的这些不同变化导致天线接收到的波的不同随机相位变化。在26兆赫的频率区域,这种影响很大。由于不同的原因,在这个频率区域的观测是重要的。由于接收波的随机相位波动、本振的随机相位漂移以及观测时间有限,从接收机获得的信号之间的相关性低于检测水平。因此,检测甚至变得不可能。由于电离层不规则斑点的周期性结构,差分电离层相位误差被建模为准正弦指数相位。差分振荡器的漂移被建模为具有随机斜率的线性变化。最后,将总差相误差表示为具有近似参数的矩阵方程。应用递归卡尔曼滤波算法对矩阵方程进行了真相位估计。利用新相位重构相关函数。这一过程在很大程度上提高了信噪比。该方法已应用于射电星3C144上,取得了很好的结果。由于近来计算机处理速度的提高,这种方法似乎很有价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State space method for reducing phase fluctuations for the radio waves travelling through the ionosphere at 26 MHz
In this work one of the most important problems in the radio astronomy has been attacked. In radio astronomy antenna arrays are used with very long baselines in order to obtain good angular resolutions. For the baseline of 3000 km the two element array gives an effect of a parabolic antenna as if it has 3000 km radius. The antennas see different parts of the Ionosphere because of the large distance between the antennas. These different regions seen by the two antennas have different random dynamic structures with a small correlation of these dynamic time varying structures. These different changes in two different regions of the Ionosphere cause different random phase changes of received waves by the antennas. The effects are large for the frequencies at 26 MHz regions. The observations are important at this frequency region for different reasons. Because of the random phase fluctuations of the received waves, random phase drifts of the local oscillators and the limited observation time, the correlation between the signals obtained from the receivers is below the detection level. Therefore, detection becomes even impossible. In this work, the differential ionospheric phase error is modeled as quasi-sinusoidal exponential phase because of the periodic structure of ionospheric irregularity blobs. The differential oscillator drift is modeled as a linear change with a random slope. Finally, the total differential phase error is expressed as a matrix equation with approximate parameters. Applying the recursive Kalman Filter algorithm to the matrix equation the true phase is estimated. With the new phase, the correlation function is reconstructed. This process improved the S/N ratio in great extends. The method has been applied to the radio star 3C144 and very good results have been obtained. Because of improvements in the processing speeds of the computers lately, the method seems to be valuable.
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