Time dependence of noise characteristics in continuous GPS observations from East Africa

Yelebe Birhanu; Simon Williams; Rebecca Bendick; Shimeles Fisseha

doi:10.1016/j.jafrearsci.2018.04.015

Time dependence of noise characteristics in continuous GPS observations from East Africa

Yelebe Birhanu, Simon Williams, Rebecca Bendick, Shimeles Fisseha

Geosciences

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

A noise model for the regional continuous GPS (cGPS) timeseries in East Africa (Ethiopia and Eritrea) was computed using the maximum likelihood estimation (MLE) method. Using this method and assigning different noise models for each cGPS site and each component (north, east and vertical) may bias the noise level of the velocity solutions due to the non-uniformity of the length of the timeseries. Within the whole regional network, the length of the timeseries varies from one to seven years. We compute a preferred regional noise model for the whole data sets using a stacked maximum likelihood values for the different power – law indexes (between −2 and 0 with a time step of 0.1), presuming that there is only one noise model that exists in the regional cGPS timeseries. Therefore, a single power – law index (flicker plus white noise) was assigned for the whole regional network irrespective of the length of the timeseries. This approach is more robust and “realistic” to determine the noise characteristics of the regional GPS network.

Original language	English
Pages (from-to)	83-89
Number of pages	7
Journal	Journal of African Earth Sciences
Volume	144
DOIs	https://doi.org/10.1016/j.jafrearsci.2018.04.015
State	Published - Aug 2018

Funding

This work is supported by NSF EAR-1119209 and NERC funding through RiftVolc NE/L013932/1 . We would like to thank Institute of Geophysics, Space Sciences and Astronomy, Addis Ababa University and Eritrean Institute of Technology. Data are archived in the UNAVCO archive. This work is supported by NSF EAR-1119209 and NERC funding through RiftVolc NE/L013932/1. We would like to thank Institute of Geophysics, Space Sciences and Astronomy, Addis Ababa University and Eritrean Institute of Technology. Data are archived in the UNAVCO archive.

Funders	Funder number
EAR-1119209
Natural Environment Research Council	noc010012
NE/L013932/1
National Stroke Foundation, Australia

Keywords

Maximum likelihood
Noise model
Power – law index
Timeseries

Access to Document

10.1016/j.jafrearsci.2018.04.015

Cite this

@article{db44afba9d1e49c8814e67da3bf77109,

title = "Time dependence of noise characteristics in continuous GPS observations from East Africa",

abstract = "A noise model for the regional continuous GPS (cGPS) timeseries in East Africa (Ethiopia and Eritrea) was computed using the maximum likelihood estimation (MLE) method. Using this method and assigning different noise models for each cGPS site and each component (north, east and vertical) may bias the noise level of the velocity solutions due to the non-uniformity of the length of the timeseries. Within the whole regional network, the length of the timeseries varies from one to seven years. We compute a preferred regional noise model for the whole data sets using a stacked maximum likelihood values for the different power – law indexes (between −2 and 0 with a time step of 0.1), presuming that there is only one noise model that exists in the regional cGPS timeseries. Therefore, a single power – law index (flicker plus white noise) was assigned for the whole regional network irrespective of the length of the timeseries. This approach is more robust and “realistic” to determine the noise characteristics of the regional GPS network.",

keywords = "Maximum likelihood, Noise model, Power – law index, Timeseries",

author = "Yelebe Birhanu and Simon Williams and Rebecca Bendick and Shimeles Fisseha",

note = "Publisher Copyright: {\textcopyright} 2018 Elsevier Ltd",

year = "2018",

month = aug,

doi = "10.1016/j.jafrearsci.2018.04.015",

language = "English",

volume = "144",

pages = "83--89",

journal = "Journal of African Earth Sciences",

issn = "1464-343X",

publisher = "Elsevier Ltd",

}

TY - JOUR

T1 - Time dependence of noise characteristics in continuous GPS observations from East Africa

AU - Birhanu, Yelebe

AU - Williams, Simon

AU - Bendick, Rebecca

AU - Fisseha, Shimeles

PY - 2018/8

Y1 - 2018/8

N2 - A noise model for the regional continuous GPS (cGPS) timeseries in East Africa (Ethiopia and Eritrea) was computed using the maximum likelihood estimation (MLE) method. Using this method and assigning different noise models for each cGPS site and each component (north, east and vertical) may bias the noise level of the velocity solutions due to the non-uniformity of the length of the timeseries. Within the whole regional network, the length of the timeseries varies from one to seven years. We compute a preferred regional noise model for the whole data sets using a stacked maximum likelihood values for the different power – law indexes (between −2 and 0 with a time step of 0.1), presuming that there is only one noise model that exists in the regional cGPS timeseries. Therefore, a single power – law index (flicker plus white noise) was assigned for the whole regional network irrespective of the length of the timeseries. This approach is more robust and “realistic” to determine the noise characteristics of the regional GPS network.

AB - A noise model for the regional continuous GPS (cGPS) timeseries in East Africa (Ethiopia and Eritrea) was computed using the maximum likelihood estimation (MLE) method. Using this method and assigning different noise models for each cGPS site and each component (north, east and vertical) may bias the noise level of the velocity solutions due to the non-uniformity of the length of the timeseries. Within the whole regional network, the length of the timeseries varies from one to seven years. We compute a preferred regional noise model for the whole data sets using a stacked maximum likelihood values for the different power – law indexes (between −2 and 0 with a time step of 0.1), presuming that there is only one noise model that exists in the regional cGPS timeseries. Therefore, a single power – law index (flicker plus white noise) was assigned for the whole regional network irrespective of the length of the timeseries. This approach is more robust and “realistic” to determine the noise characteristics of the regional GPS network.

KW - Maximum likelihood

KW - Noise model

KW - Power – law index

KW - Timeseries

UR - https://www.scopus.com/pages/publications/85047483014

U2 - 10.1016/j.jafrearsci.2018.04.015

DO - 10.1016/j.jafrearsci.2018.04.015

M3 - Article

AN - SCOPUS:85047483014

SN - 1464-343X

VL - 144

SP - 83

EP - 89

JO - Journal of African Earth Sciences

JF - Journal of African Earth Sciences

ER -

Time dependence of noise characteristics in continuous GPS observations from East Africa

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this