TY - GEN
T1 - Statistical signal processing approach for rain estimation based on measurements from network management systems
AU - Ostrometzky, Jonatan
AU - Messer, Hagit
N1 - Publisher Copyright: © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2020/5
Y1 - 2020/5
N2 - In this paper we apply statistical signal processing methodologies on a real-world application of using Commercial Microwave Links (CMLs) as opportunistic sensors for rain monitoring. We formulate an appropriate parameter estimation problem, taking advantage on the empirically evaluated statistics of the rain, and present a new methodology for rain estimation given only the quantized minimum and maximum radio signal level measurements, which are being logged regularly by the network management systems. Our method transforms measurements taken from any single CML, without the need for training series, nor any prior or side information, into rainfall estimates, that is - to a virtual rain gauge. The operation of the proposed method was demonstrated using actual CMLs in Israel in a semiarid climate zone, and shows that the achieved rain estimates agrees with near-by dedicated rain gauges.
AB - In this paper we apply statistical signal processing methodologies on a real-world application of using Commercial Microwave Links (CMLs) as opportunistic sensors for rain monitoring. We formulate an appropriate parameter estimation problem, taking advantage on the empirically evaluated statistics of the rain, and present a new methodology for rain estimation given only the quantized minimum and maximum radio signal level measurements, which are being logged regularly by the network management systems. Our method transforms measurements taken from any single CML, without the need for training series, nor any prior or side information, into rainfall estimates, that is - to a virtual rain gauge. The operation of the proposed method was demonstrated using actual CMLs in Israel in a semiarid climate zone, and shows that the achieved rain estimates agrees with near-by dedicated rain gauges.
KW - Applications of statistical signal processing techniques
KW - Remote sensing of the environment
UR - http://www.scopus.com/inward/record.url?scp=85091323315&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ICASSP40776.2020.9054652
DO - https://doi.org/10.1109/ICASSP40776.2020.9054652
M3 - منشور من مؤتمر
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 9026
EP - 9030
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -