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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Inverse Modeling of GPS Multipath for Snow Depth Estimation—Part I: Formulation and Simulations
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Inverse Modeling of GPS Multipath for Snow Depth Estimation—Part I: Formulation and Simulations

机译：GPS多径雪深估计的逆建模—第一部分：公式与仿真

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摘要

Snowpacks provide reservoirs of freshwater. The amount stored and how fast it is released by melting are vital information for both scientists and water supply managers. GPS multipath reflectometry (GPS-MR) is a new technique that can be used to measure snow depth. Signal-to-noise ratio data collected by GPS instruments exhibit peaks and troughs as coherent direct and reflected signals go in and out of phase. These interference fringes are used to retrieve the unknown land surface characteristics. In this two-part contribution, a forward/inverse approach is offered for GPS-MR of snow depth. Part I starts with the physically based forward model utilized to simulate the coupling of the surface and antenna responses. A statistically rigorous inverse model is presented and employed to retrieve parameter corrections responsible for observation residuals. The unknown snow characteristics are parameterized, the observation/parameter sensitivity is illustrated, the inversion performance is assessed in terms of its precision and its accuracy, and the dependence of model results on the satellite direction is quantified. The latter serves to indicate the sensing footprint of the reflection.
机译：积雪堆提供淡水蓄水池。对于科学家和供水经理而言，储存的量及其融化释放的速度都是至关重要的信息。 GPS多径反射法（GPS-MR）是一项可用于测量雪深的新技术。 GPS仪器收集的信噪比数据会出现波峰和波谷，因为相干的直接信号和反射信号会进入相位和进入相位。这些干涉条纹用于检索未知的陆地表面特征。在这一由两部分组成的贡献中，为雪深的GPS-MR提供了一种正向/反向方法。第一部分从基于物理的正向模型开始，该模型用于模拟表面和天线响应的耦合。提出了统计上严格的逆模型，并将其用于检索引起观测残差的参数校正。对未知的降雪特征进行参数化，说明观测/参数灵敏度，根据其精度和准确性评估反演性能，并量化模型结果对卫星方向的依赖性。后者用于指示反射的感应足迹。

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