THE POTENTIAL OF SMARTLNB NETWORKS FOR RAINFALL ESTIMATION

被引：0

作者：

Giannetti, Filippo ^{[1
]}

Moretti, Marco ^{[1
]}

Reggiannini, Ruggero ^{[1
]}

Petrolino, Antonio ^{[2
]}

Bacci, Giacomo ^{[2
]}

Adirosi, Elisa ^{[3
]}

Baldini, Luca ^{[3
]}

Facheris, Luca ^{[3
]}

Melani, Samantha ^{[4
]}

Ortolani, Alberto ^{[4
]}

机构：

[1] Univ Pisa, Pisa, Italy

[2] MBI Srl, Pisa, Italy

[3] CNIT Lab Nazl Radar & Sistemi Sorveglianza, Pisa, Italy

[4] CNR IBIMET, Florence, Italy

来源：

2018 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) | 2018年

关键词：

Rain attenuation in satellite links; Kalman filter; rain fields evaluation; nowcasting;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

NEFOCAST is a research project that aims at retrieving rainfall fields from channel attenuation measurements on satellite links. Rainfall estimation algorithms rely on the deviation of the measured E-s/N-0 from the clear-sky conditions. Unfortunately, clear-sky measurements exhibit signal fluctuations (due to a variety of causes) which could generate false rain detections and reduce estimation accuracy. In this paper we first review the main causes of random amplitude fluctuations in the received E-s/N-0, and then we present an adaptive tracking algorithm based on two Kalman filters: one that tracks slow changes in E-s/N-0 due to external causes and another which tracks fast E-s/N-0 variations due to rain. A comparison of the outputs of the two filters confirms the reliability of the rainfall rate estimate.

引用

页码：120 / 124

页数：5

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