GNSS-IR Sea Level Retrieval Combining Quality Control with Inter-Frequency Bias Correction
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摘要: 全球导航卫星系统干涉反射测量(GNSS-IR)技术已被证实可用于海面测高， 为提升 GNSSIR 海面高度反演精度，本文在常用 SNR 频谱质量控制方法的基础上，提出考虑频谱峰值尖锐程度的质量控制新方法，联合对初始反演结果进行质量控制， 利用质量控制新方法定权与频间偏差改正建立顾及频间偏差二阶动态海面改正模型，实现对初始反演结果的多频多系统数据融合与误差改正。 通过处理美国 SC02 和中国香港 HKQT 两个测站 GNSS 数据， 分析实验结果表明：使用了质量控制新方法可有效控制粗差出现，较未使用前精度普遍提升 1 cm 以上； 使用顾及频间偏差二阶动态海面改正模型对初始反演结果进行处理，反演精度提升 3 cm 以上，在观测环境、数据质量良好的情况下 GNSS-IR 海面高度反演精度可达厘米级，但在风速超过 20 m/s 以上情况下反演结果较差；在较大时间窗条件下，本文所建模型比一阶模型具有更优的动态海面改正效果，反演精度则比未顾及频间偏差模型有明显提升，验证了该模型的可用性。Abstract: Objectives: Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has been proved to be able to monitor sea level. Improving accuracy is the key to GNSS-IR sea level retrieval based on signal-to-noise ratio (SNR) data. Method: This paper proposes a new quality control method considering the sharpness of spectrum peak on the basis of the common SNR spectrum quality control methods, which those methods jointly control the quality of the initial retrievals. Then a second-order dynamic sea surface correction model considering inter-frequency bias is established by combining the new quality control method used for weighting with inter-frequency bias correction, which is realizes multi-frequency multi-system data fusion and error correction of initial retrievals. Results: The GNSS data collected from SC02 in USA and HKQT in China's Hong Kong was processed in the experiment. The accuracy of initial retrievals is generally improved by more than 1 cm after using the new quality control method. The second-order dynamic sea surface correction model considering inter-frequency bias is applied to initial retrievals and improves accuracy by more than 3 cm. When the observation environment and data quality are favorable, the accuracy of GNSS-IR sea level retrieval reach centimeter level, but the retrievals are poor when the wind speed is more than 20 m/s. Under the circumstance of larger time window, the model proposed in this paper has better dynamic sea surface correction effect than the firstorder model, and the retrieval accuracy is significantly improved than the model without taking into account the inter-frequency bias. Conclusion: The new quality control method can effectively control the occurrence of gross errors. The second-order dynamic sea surface correction model considering inter-frequency bias has better correction effect than the conventional first-order model and the model without considering the inter-frequency bias.
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Keywords:
- GNSS-IR /
- SNR /
- sea level /
- quality control /
- inter-frequency bias /
- dynamic sea surface correction
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