A Field Assessment of a Rain Estimation System Based on Satellite-to-Earth Microwave Links

Colli, Matteo; Stagnaro, Mattia; Caridi, Andrea; Lanza, Luca G.; Randazzo, Andrea; Pastorino, Matteo; Caviglia, Daniele D.; Delucchi, Alessandro

doi:10.1109/tgrs.2018.2878338

Cited by 21 publications

(24 citation statements)

References 16 publications

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“…Inspired by the utilization of HMLs, the oblique earth-space links (OELs) between ground and satellite have been studied for rainfall monitoring [22][23][24][25]. As another source of microwave links, the deployment of the OELs rainfall observation system cannot only use the existing equipment but also has a lower installation cost [26].…”

Section: Introductionmentioning

confidence: 99%

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

et al. 2020

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High-precision rainfall field reconstruction and nowcasting play an important role in many aspects of social life. In recent years, the rain-induced signal attenuation of oblique earth-space links (OELs) has been presented to monitor regional rainfall. In this paper, we set up the first OEL in Nanjing, China, for the estimation of rain intensity. A year of observations from this link are also compared with the measurements from laser disdrometer OTT-Parsivel (OTT), between which the correlation is 0.86 and the determination coefficient is 0.73. Then, the simulation experiment is carried out: an OELs network is built, and the Kriging interpolation algorithm is employed to perform rainfall field reconstruction. The rainfall fields of plum rain season from 2016 to 2019 have been reconstructed by this network, which shows a good agreement with satellite remote sensing data. The resulting root-mean-square errors are lower than 3.46 mm/h and spatial correlations are higher than 0.80. Finally, we have achieved the nowcasting of rainfall field based on a machine-learning approach, especially deep learning. It can be seen from experiment results that the motion of rain cell and the position of peak rain intensity are predicted successfully, which is of great significant for taking concerted actions in case of emergency. Our experiment demonstrates that the densely distributed OELs are expected to become a futuristic rainfall monitoring system complementing existing weather radar and rain gauge observation networks.

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Section: Introductionmentioning

confidence: 99%

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

et al. 2020

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“…In this respect, it is worth remarking that the Due to their constant transmit power, beacons represent an excellent reference for the measurement of the fluctuations in received signal strength caused by propagation phenomena. Figure 6 depicts the high-level conceptual scheme of the beacon-based measurement system, which was adopted by many authors [6,[47][48][49][50][51]. After the RF front-end, a CW beacon is prefiltered by a narrowband band-pass filter centered around the beacon frequency.…”

Section: Beacon Power Measurementmentioning

confidence: 99%

“…Furthermore, depending on how the low-pass filter for smoothing out fast fluctuations is designed, a delay in rain detection may be introduced where it is not always compatible with the real-time response requirement of certain applications. For instance, in [1,6,49], sliding window filters are used with response latency in the order of tens of minutes.…”

Section: Identification Of the Rainy Periodsmentioning

confidence: 99%

“…As for the determination of the dry baseline in the dry periods, in the previous section we have already provided a review of the main techniques proposed in the literature to carry out this task [1,5,8,49]. They differ from one another mainly for the various approaches devised to counteract the slow fluctuations affecting the measurements of the performance parameter under the dry state assumption.…”

Section: Identification Of the Dry Baseline During Dry And Rainy Periodsmentioning

confidence: 99%

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Opportunistic Rain Rate Estimation from Measurements of Satellite Downlink Attenuation: A Survey

Giannetti

Reggiannini

2021

Sensors

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Recent years have witnessed a growing interest in techniques and systems for rainfall surveillance on regional scale, with increasingly stringent requirements in terms of the following: (i) accuracy of rainfall rate measurements, (ii) adequate density of sensors over the territory, (iii) space-time continuity and completeness of data and (iv) capability to elaborate rainfall maps in near real time. The devices deployed to monitor the precipitation fields are traditionally networks of rain gauges distributed throughout the territory, along with weather radars and satellite remote sensors operating in the optical or infrared band, none of which, however, are suitable for full compliance to all of the requirements cited above. More recently, a different approach to rain rate estimation techniques has been proposed and investigated, based on the measurement of the attenuation induced by rain on signals of pre-existing radio networks either in terrestrial links, e.g., the backhaul connections in cellular networks, or in satellite-to-earth links and, among the latter, notably those between geostationary broadcast satellites and domestic subscriber terminals in the Ku and Ka bands. Knowledge of the above rain-induced attenuation permits the retrieval of the corresponding rain intensity provided that a number of meteorological and geometric parameters are known and ultimately permits estimating the rain rate locally at the receiver site. In this survey paper, we specifically focus on such a type of “opportunistic” systems for rain field monitoring, which appear very promising in view of the wide diffusion over the territory of low-cost domestic terminals for the reception of satellite signals, prospectively allowing for a considerable geographical capillarity in the distribution of sensors, at least in more densely populated areas. The purpose of the paper is to present a broad albeit synthetic overview of the numerous issues inherent in the above rain monitoring approach, along with a number of solutions and algorithms proposed in the literature in recent years, and ultimately to provide an exhaustive account of the current state of the art. Initially, the main relevant aspects of the satellite link are reviewed, including those related to satellite dynamics, frequency bands, signal formats, propagation channel and radio link geometry, all of which have a role in rainfall rate estimation algorithms. We discuss the impact of all these factors on rain estimation accuracy while also highlighting the substantial differences inherent in this approach in comparison with traditional rain monitoring techniques. We also review the basic formulas relating rain rate intensity to a variation of the received signal level or of the signal-to-noise ratio. Furthermore, we present a comprehensive literature survey of the main research issues for the aforementioned scenario and provide a brief outline of the algorithms proposed for their solution, highlighting their points of strength and weakness. The paper includes an extensive list of bibliographic references from which the material presented herein was taken.

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“…This aspect has been already highlighted by other works [2,11]: clearly, a large-scale diffusion of water wireless sensing networks can only be achieved if the unitary cost of the nodes is affordable. A similar paradigm, in which the spatio-temporal resolution of environmental monitoring maps is significantly improved by the diffusion of low-cost measuring units and participatory sensing, based on emerging miniaturized technologies and complementary to the few (often fixed) governmental reference monitoring stations, has been observed in monitoring air quality [32], radioactivity [33,34], and local forecasting of rainfalls [35].…”

Section: Introductionmentioning

confidence: 99%

A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems

Carminati

Turolla

Mezzera

et al. 2020

Sensors

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A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.

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A Field Assessment of a Rain Estimation System Based on Satellite-to-Earth Microwave Links

Cited by 21 publications

References 16 publications

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

Opportunistic Rain Rate Estimation from Measurements of Satellite Downlink Attenuation: A Survey

A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems

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