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A new iterative algorithm for ionospheric tomography

机译:电离层层析成像的一种新的迭代算法

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An ionospheric tomography system consists of a satellite and several ground stations located in a line under the path of the satellite. The data collected at the ground stations are the integrals of electron density along many paths between the ground stations and the satellite. From this data an image of electron density in the plane defined by the satellite orbit and the ground stations can be reconstructed using tomographic techniques. However, the data obtained from an ionospheric tomography system is not complete, so a priori information must be used in the reconstruction algorithm in order to obtain a useful solution. The orthogonal decomposition algorithm (ODA) provides a way of incorporating a priori information into the reconstruction. However, due to problems with numerical conditioning, ODA by itself does not yield a solution. This paper presents a new algorithm for ionospheric tomography reconstruction called the recursive correction method (RCM). RCM is a fast, stable, iterative algorithm that takes advantage of the special structure of the ionospheric tomography problem. This paper will also present convergence analysis of RCM, comparison between RCM and algebraic reconstruction technique (ART), and an example using simulated data.
机译:电离层层析成像系统由卫星和位于卫星路径下方一条线上的几个地面站组成。在地面站收集的数据是沿着地面站与卫星之间的许多路径的电子密度的积分。根据该数据,可以使用层析成像技术在由卫星轨道和地面站定义的平面中重建电子密度图像。但是,从电离层层析成像系统获得的数据不完整,因此在重建算法中必须使用先验信息以获得有用的解决方案。正交分解算法(ODA)提供了一种将先验信息合并到重建中的方法。但是,由于数值条件的问题,ODA本身无法解决。本文提出了一种用于电离层层析成像重建的新算法,称为递归校正方法(RCM)。 RCM是一种快速,稳定,迭代的算法,它利用了电离层层析成像问题的特殊结构。本文还将介绍RCM的收敛性分析,RCM与代数重建技术(ART)的比较以及使用模拟数据的示例。

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