A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR

Endrit Shehaj, K. Wilgan, O. Frey, A. Geiger
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引用次数: 6

Abstract

High spatio-temporal variability of atmospheric water vapor affects microwave signals of Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). A better knowledge of the distribution of water vapor improves both GNSS- and InSAR-derived data products. In this work, we present a collocation framework to combine and retrieve zenith and (relative) slant tropospheric delays. GNSS and InSAR meteorological products are combined aiming at a better retrieval of the atmospheric water vapor. We investigate the combination approach with synthetic and real data acquired in the Alpine region of Switzerland. Based on a closed-loop validation with simulated delays, a few mm accuracy is achieved for the GNSS-InSAR combination in terms of retrieved ZTDs. Furthermore, when real delays are collocated, the combination results are more congruent with InSAR computed products. This research is a contribution to improve the spatio-temporal mapping of tropospheric delays by combining GNSS-derived and InSAR-derived delays.
从GNSS和InSAR组合中检索对流层延迟的配置框架
大气水汽的高时空变异性影响全球导航卫星系统(GNSS)和干涉合成孔径雷达(InSAR)的微波信号。更好地了解水蒸气的分布可以改进GNSS和InSAR衍生的数据产品。在这项工作中,我们提出了一个组合和检索天顶和(相对)倾斜对流层延迟的配置框架。GNSS和InSAR气象产品的结合旨在更好地检索大气水蒸气。我们研究了在瑞士阿尔卑斯地区获得的合成和真实数据的组合方法。基于具有模拟延迟的闭环验证,就检索到的ZTD而言,GNSS InSAR组合实现了几毫米的精度。此外,当实际延迟被并置时,组合结果与InSAR计算的乘积更加一致。这项研究通过结合GNSS衍生的延迟和InSAR衍生的延迟,为改进对流层延迟的时空映射做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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