Tsunami detection based on noisy sea surface height measurement

Kegen Yu

doi:10.1109/IGARSS.2016.7730258

Tsunami detection based on noisy sea surface height measurement

Kegen Yu^*

^*Corresponding author for this work

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

Abstract

This paper presents an approach for the detection of early weak Tsunami in presence of large noise in sea surface height (SSH) measurements obtained such as using a satellite-carried global navigation satellite system (GNSS) receiver and the GNSS reflectometry (GNSS-R) technique. A sliding window moving average (SWMA) technique is proposed for detecting a Tsunami lead wave and a hypothesis testing method is developed to decide whether or not a Tsunami is present by examining the SWMA outputs against a predefined threshold. The proposed approach is evaluated using the 2011 Japan's Tsunami data collected by altimetry satellite Jason-1. Simulation results demonstrate that the proposed detect method considerably outperforms the existing methods.

Original language	English
Title of host publication	2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	4823-4826
Number of pages	4
ISBN (Electronic)	9781509033324
DOIs	https://doi.org/10.1109/IGARSS.2016.7730258
Publication status	Published - 1 Nov 2016
Externally published	Yes
Event	36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China Duration: 10 Jul 2016 → 15 Jul 2016

Other

Other	36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/Territory	China
City	Beijing
Period	10/07/16 → 15/07/16

Keywords

GNSS-R
hypothesis testing
sea surface height measurement
sliding window moving average
Tsunami detection

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10.1109/IGARSS.2016.7730258

Cite this

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title = "Tsunami detection based on noisy sea surface height measurement",

abstract = "This paper presents an approach for the detection of early weak Tsunami in presence of large noise in sea surface height (SSH) measurements obtained such as using a satellite-carried global navigation satellite system (GNSS) receiver and the GNSS reflectometry (GNSS-R) technique. A sliding window moving average (SWMA) technique is proposed for detecting a Tsunami lead wave and a hypothesis testing method is developed to decide whether or not a Tsunami is present by examining the SWMA outputs against a predefined threshold. The proposed approach is evaluated using the 2011 Japan's Tsunami data collected by altimetry satellite Jason-1. Simulation results demonstrate that the proposed detect method considerably outperforms the existing methods.",

keywords = "GNSS-R, hypothesis testing, sea surface height measurement, sliding window moving average, Tsunami detection",

author = "Kegen Yu",

year = "2016",

month = nov,

day = "1",

doi = "10.1109/IGARSS.2016.7730258",

language = "English",

pages = "4823--4826",

booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",

}

Yu, K 2016, Tsunami detection based on noisy sea surface height measurement. in 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings., 7730258, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 4823-4826, 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016, Beijing, China, 10/07/16. https://doi.org/10.1109/IGARSS.2016.7730258

Tsunami detection based on noisy sea surface height measurement. / Yu, Kegen.
2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 4823-4826 7730258.

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

TY - GEN

T1 - Tsunami detection based on noisy sea surface height measurement

AU - Yu, Kegen

PY - 2016/11/1

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N2 - This paper presents an approach for the detection of early weak Tsunami in presence of large noise in sea surface height (SSH) measurements obtained such as using a satellite-carried global navigation satellite system (GNSS) receiver and the GNSS reflectometry (GNSS-R) technique. A sliding window moving average (SWMA) technique is proposed for detecting a Tsunami lead wave and a hypothesis testing method is developed to decide whether or not a Tsunami is present by examining the SWMA outputs against a predefined threshold. The proposed approach is evaluated using the 2011 Japan's Tsunami data collected by altimetry satellite Jason-1. Simulation results demonstrate that the proposed detect method considerably outperforms the existing methods.

AB - This paper presents an approach for the detection of early weak Tsunami in presence of large noise in sea surface height (SSH) measurements obtained such as using a satellite-carried global navigation satellite system (GNSS) receiver and the GNSS reflectometry (GNSS-R) technique. A sliding window moving average (SWMA) technique is proposed for detecting a Tsunami lead wave and a hypothesis testing method is developed to decide whether or not a Tsunami is present by examining the SWMA outputs against a predefined threshold. The proposed approach is evaluated using the 2011 Japan's Tsunami data collected by altimetry satellite Jason-1. Simulation results demonstrate that the proposed detect method considerably outperforms the existing methods.

KW - GNSS-R

KW - hypothesis testing

KW - sea surface height measurement

KW - sliding window moving average

KW - Tsunami detection

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DO - 10.1109/IGARSS.2016.7730258

M3 - Conference proceeding contribution

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SP - 4823

EP - 4826

BT - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016

Y2 - 10 July 2016 through 15 July 2016

ER -

Tsunami detection based on noisy sea surface height measurement

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