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首页> 外文期刊>Radio Science >Dynamic error estimation for radio occultation bending angles retrieved by the full spectrum inversion technique
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Dynamic error estimation for radio occultation bending angles retrieved by the full spectrum inversion technique

机译:全频谱反演技术获取的无线电掩星弯曲角度的动态误差估计

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摘要

Application of any measurement requires reliable error estimates; this is particularly the case when meteorological observations are assimilated into numerical weather prediction models. Radio occultation measurement errors vary considerably between different observations. It is therefore desirable to estimate these errors dynamically on a profile-to-profile basis. In this study it is demonstrated that fluctuations in the full spectrum inversion (FSI) log amplitude can be mapped into profiles of error standard deviations for FSI retrieved bending angles on a profile-to-profile basis without using any external data. The performance of this technique is assessed by applying it to simulated GPS radio occultation signals sampled at 50 Hz with both severe additive noise and significant phase noise. In both cases, good agreement between predicted error profiles and the “true” error profiles is achieved. Comparisons between power spectra of predicted errors and “true” errors also show good agreement. However, a small part of the simulated signals is distorted by aliasing due to the downsampling to 50 Hz, which affects bending angles retrieved for a narrow range of impact parameters. For these bending angles, the predicted errors are too small as compared with the “true” errors. This shows that the proposed technique cannot predict errors related to poor signal acquisition.
机译:应用任何测量都需要可靠的误差估计;当将气象观测值纳入数值天气预报模型时,尤其如此。在不同的观测之间,无线电掩星的测量误差差异很大。因此,期望基于配置文件到配置文件动态地估计这些误差。在这项研究中,证明了在不使用任何外部数据的情况下,可以将FSI取回的弯曲角度的全光谱反转(FSI)对数幅度的波动映射到误差标准偏差的轮廓中。通过将该技术应用于以50 Hz采样的模拟GPS无线电掩星信号,同时具有严重的加性噪声​​和明显的相位噪声,可以评估该技术的性能。在这两种情况下,都可以在预测的误差分布图和“真实”误差分布图之间取得良好的一致性。预测误差和“真实”误差的功率谱之间的比较也显示出很好的一致性。但是,由于降采样至50 Hz,一小部分模拟信号会因混叠而失真,这会影响在较窄范围的冲击参数下检索到的弯曲角度。对于这些弯曲角度,与“真实”误差相比,预测误差太小。这表明所提出的技术不能预测与不良信号采集有关的误差。

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