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Joint Inversion of Atmospheric Refractivity Profile Based on Ground-Based GPS Phase Delay and Propagation Loss

机译:基于地基GPS相位延迟和传播损耗的大气折射率剖面联合反演

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In this paper, we present a new estimation of the atmospheric refractivity profile combining the scattering signal (electromagnetic wave propagation loss) and the direct signal (phase delay). The refractivity profile is modeled using four parameters, i.e. , the gradient of the refractivity profile ( c 1 , c 2 ) and the vertical altitude ( h 1 , h 2 ). We apply the NSGA-II (Non-dominated Sorting Genetic Algorithm II), a multiobjective optimization algorithm, to achieve the goals of joint optimization inversion in the inverting process, and compare this method with traditional individual inversion methods. The anti-noise ability of joint inversion is investigated under the noiseless condition and adding noise condition, respectively. The numerical experiments demonstrate that joint inversion is superior to individual inversion. The adding noise test further suggests that this method can estimate synthesized parameters more efficiently and accurately in different conditions. Finally, a set of measured data is tested in the new way and the consequence of inversion shows the joint optimization inversion algorithm has feasibility, effectiveness and superiority in the retrieval of the refractivity profile.
机译:在本文中,我们结合散射信号(电磁波传播损耗)和直接信号(相位延迟)提出了一种大气折射率分布的新估计。折射率分布是使用四个参数建模的,即折射率分布的梯度(c 1,c 2)和垂直高度(h 1,h 2)。我们将多目标优化算法NSGA-II(非主导排序遗传算法II)用于实现逆过程中联合优化反演的目标,并将此方法与传统的个体反演方法进行比较。分别在无噪声和加噪声条件下研究了联合反演的抗噪能力。数值实验表明联合反演优于个体反演。附加噪声测试进一步表明,该方法可以在不同条件下更有效,更准确地估计合成参数。最后,以新的方式测试了一组测量数据,反演的结果表明,联合优化反演算法在折射率分布的检索中具有可行性,有效性和优越性。

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