The use of linear feature projection for precipitation classification using measurements from commercial microwave links

Dani Cherkassky; Jonatan Ostrometzky; Hagit Messer

doi:10.1007/978-3-642-28551-6_63

The use of linear feature projection for precipitation classification using measurements from commercial microwave links

Dani Cherkassky, Jonatan Ostrometzky, Hagit Messer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

High frequency electromagnetic waves are highly influenced by atmospheric conditions, namely wireless microwave links with carrier frequency of tens of GHz can be used for precipitation monitoring. In the scope of this paper we present a novel detection/classification system capable of detecting wet periods, with the ability to classify the precipitation type as rain or sleet, given an attenuation signal from spatially distributed wireless commercial microwave links. Fade (attenuation) dynamics was selected as a discriminating feature providing the data for classification. Linear Feature Extraction method is formulated; thereafter, the efficiency is evaluated based on real data. The detection/classification system is based on the Fisher's linear discriminant and likelihood ratio test. Its performance is demonstrated using actual Received Signal Level measurements from a cellular backhaul network in the northern part of Israel. In particular, the use of the raw data as well as its derivatives to achieve better classification performance is suggested.

Original language	English
Title of host publication	Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings
Pages	511-519
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-28551-6_63
State	Published - 2012
Externally published	Yes
Event	10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012 - Tel Aviv, Israel Duration: 12 Mar 2012 → 15 Mar 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7191 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012
Country/Territory	Israel
City	Tel Aviv
Period	12/03/12 → 15/03/12

Bibliographical note

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

Keywords

Environmental monitoring
Received Signal Level (RSL) measurements
fade dynamics
feature extraction
rain sleet events classification/detection

Access to Document

10.1007/978-3-642-28551-6_63

Cite this

Cherkassky, D., Ostrometzky, J., & Messer, H. (2012). The use of linear feature projection for precipitation classification using measurements from commercial microwave links. In Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings (pp. 511-519). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7191 LNCS). https://doi.org/10.1007/978-3-642-28551-6_63

Cherkassky, Dani ; Ostrometzky, Jonatan ; Messer, Hagit. / The use of linear feature projection for precipitation classification using measurements from commercial microwave links. Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings. 2012. pp. 511-519 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "The use of linear feature projection for precipitation classification using measurements from commercial microwave links",

abstract = "High frequency electromagnetic waves are highly influenced by atmospheric conditions, namely wireless microwave links with carrier frequency of tens of GHz can be used for precipitation monitoring. In the scope of this paper we present a novel detection/classification system capable of detecting wet periods, with the ability to classify the precipitation type as rain or sleet, given an attenuation signal from spatially distributed wireless commercial microwave links. Fade (attenuation) dynamics was selected as a discriminating feature providing the data for classification. Linear Feature Extraction method is formulated; thereafter, the efficiency is evaluated based on real data. The detection/classification system is based on the Fisher's linear discriminant and likelihood ratio test. Its performance is demonstrated using actual Received Signal Level measurements from a cellular backhaul network in the northern part of Israel. In particular, the use of the raw data as well as its derivatives to achieve better classification performance is suggested.",

keywords = "Environmental monitoring, Received Signal Level (RSL) measurements, fade dynamics, feature extraction, rain sleet events classification/detection",

author = "Dani Cherkassky and Jonatan Ostrometzky and Hagit Messer",

note = "Copyright: Copyright 2012 Elsevier B.V., All rights reserved.; 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012 ; Conference date: 12-03-2012 Through 15-03-2012",

year = "2012",

doi = "10.1007/978-3-642-28551-6_63",

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Cherkassky, D, Ostrometzky, J & Messer, H 2012, The use of linear feature projection for precipitation classification using measurements from commercial microwave links. in Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7191 LNCS, pp. 511-519, 10th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012, Tel Aviv, Israel, 12/03/12. https://doi.org/10.1007/978-3-642-28551-6_63

The use of linear feature projection for precipitation classification using measurements from commercial microwave links. / Cherkassky, Dani; Ostrometzky, Jonatan; Messer, Hagit.
Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings. 2012. p. 511-519 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7191 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Cherkassky D, Ostrometzky J, Messer H. The use of linear feature projection for precipitation classification using measurements from commercial microwave links. In Latent Variable Analysis and Signal Separation - 10th International Conference, LVA/ICA 2012, Proceedings. 2012. p. 511-519. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28551-6_63

The use of linear feature projection for precipitation classification using measurements from commercial microwave links

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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