Rain Field Retrieval by Ground-Level Sensors of Various Types

IF 1.3 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Frontiers in signal processing Pub Date : 2022-08-17 DOI:10.3389/frsip.2022.877336
H. Messer, A. Eshel, H. Habi, S. Sagiv, X. Zheng
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引用次数: 3

Abstract

Rain gauges (RGs) have been utilized as sensors for local rain monitoring dating back to ancient Greece. The use of a network of RGs for 2D rain mapping is based on spatial interpolation that, while presenting good results in limited experimental areas, has limited scalability because of the unrealistic need to install and maintain a large quantity of sensors. Alternatively, commercial microwave links (CMLs), widely spread around the globe, have proven effective as near-ground opportunistic rain sensors. In this study, we study 2D rain field mapping using CMLs and/or RGs from a practical and a theoretical point of view, aiming to understand their inherent performance differences. We study sensor networks of either CMLs or RGs, and also a mixed network of CMLs and RGs. We show that with proper preprocessing, the rain field retrieval performance of the CML network is better than that of RGs. However, depending on the characteristics of the rain field, this performance gain can be negligible, especially when the rain field is smooth (relative to the topology of the sensor network). In other words, for a given network, the advantage of rain retrieval using a network of CMLs is more significant when the rain field is spotty.
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利用不同类型地面传感器反演雨场
雨量计(RGs)被用作监测当地雨量的传感器可以追溯到古希腊。使用RGs网络进行二维降雨测绘是基于空间插值的,虽然在有限的实验区域内呈现出良好的结果,但由于不现实地需要安装和维护大量传感器,因此可扩展性有限。另外,在全球广泛传播的商用微波链路(cml)已被证明是有效的近地机会性降雨传感器。在这项研究中,我们从实践和理论的角度研究了使用cml和/或RGs的2D雨场映射,旨在了解它们内在的性能差异。我们研究了cml或RGs的传感器网络,以及cml和RGs的混合网络。结果表明,通过适当的预处理,CML网络的雨场检索性能优于RGs网络。然而,根据雨场的特性,这种性能增益可以忽略不计,特别是当雨场是平滑的(相对于传感器网络的拓扑结构)。换句话说,对于给定的网络,当雨场是点状的时,使用cml网络进行降雨检索的优势更为显著。
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