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Application of window functions for full spectrum inversion of cross-link radio occultation data

机译:窗口函数在交叉链接无线电掩星数据全频谱反演中的应用

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The full spectrum inversion (FSI) technique allows for effective retrieval of profiles of bending angle and optical depth. These profiles are directly derived from a Fourier transform of a measured radio occulation (RO) signal. Though the entire signal is used in the FSI Fourier transform, only some fraction of the signal contributes significantly to each pair of bending angle and optical depth, whereas noise and disturbances throughout the signal contribute to the errors for all pairs of bending angle and optical depth. The impact from noise and other disturbances may be reduced if window functions are applied in the computation of individual Fourier components. In this study, it is demonstrated how window functions can be applied to the FSI technique. In the approach described here, the window functions are applied in the frequency domain, and it is demonstrated that this technique can be applied in an iterative way to further reduce the impact of noise and disturbances. To assess the merits of using window functions, we apply the windowed FSI to simulated cross-link signals. The results from the simulations show that application of window functions in the FSI technique results in some noise reduction for both white noise and a spike in the signal, whereas iterative use of the window functions was found to significantly reduce the errors from these noise sources, as compared to standard FSI retrieval. It was also found that in terms of relative errors, retrieved derivatives of optical depth are far more sensitive to signal disturbances than retrieved bending angles.
机译:全光谱反转(FSI)技术可有效检索弯曲角​​度和光学深度的轮廓。这些配置文件直接从所测量的无线电波(RO)信号的傅立叶变换中得出。尽管整个信号都用于FSI傅立叶变换,但只有一部分信号对每对弯曲角度和光学深度有显着影响,而整个信号中的噪声和干扰对所有成对弯曲角度和光学深度都会产生误差。如果在单个傅立叶分量的计算中应用了窗函数,则可以减少来自噪声和其他干扰的影响。在这项研究中,它演示了如何将窗口函数应用于FSI技术。在这里描述的方法中,窗口函数被应用在频域中,并且证明了该技术可以以迭代的方式被应用以进一步减少噪声和干扰的影响。为了评估使用窗口功能的优点,我们将窗口FSI应用于模拟的交叉链接信号。仿真结果表明,在FSI技术中应用窗函数可降低白噪声和信号尖峰的噪声,而发现迭代使用窗函数可显着降低这些噪声源的误差,与标准FSI检索相比。还发现,就相对误差而言,所获取的光学深度导数比所获取的弯曲角度对信号干扰更为敏感。

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