Use of the Comprehensive Inversion method for Swarm satellite data analysis

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Abstract

An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agency (ESA). This new algorithm improves on a previously developed version in several ways, including the ability to process groundbased observatory data, estimation of rotations describing the alignment of vector magnetometer measurements with a known reference system, and the inclusion of ionospheric induction effects due to an a priori 3-dimensional conductivity model. However, the most substantial improvements entail the application of a mechanism termed “Selective Infinite Variance Weighting” (SIVW), which mitigates the effects of non-zero mean systematic noise and allows for the exploitation of gradient information from the low-altitude Swarm satellite pair to determine small-scale lithospheric fields, and an improvement in the treatment of attitude error due to noise in star-tracking systems over previously established methods. The advanced CI algorithm is validated by applying it to synthetic data from a full simulation of the Swarm mission, where it is found to significantly exceed all mandatory and most target accuracy requirements.
Original languageEnglish
JournalEarth Planets Space
Volume65
Issue number11
Pages (from-to)1201-1222
ISSN1343-8832
DOIs
Publication statusPublished - 2013

Cite this

@article{72831cf577514fbb9045f1958c5dcd22,
title = "Use of the Comprehensive Inversion method for Swarm satellite data analysis",
abstract = "An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agency (ESA). This new algorithm improves on a previously developed version in several ways, including the ability to process groundbased observatory data, estimation of rotations describing the alignment of vector magnetometer measurements with a known reference system, and the inclusion of ionospheric induction effects due to an a priori 3-dimensional conductivity model. However, the most substantial improvements entail the application of a mechanism termed “Selective Infinite Variance Weighting” (SIVW), which mitigates the effects of non-zero mean systematic noise and allows for the exploitation of gradient information from the low-altitude Swarm satellite pair to determine small-scale lithospheric fields, and an improvement in the treatment of attitude error due to noise in star-tracking systems over previously established methods. The advanced CI algorithm is validated by applying it to synthetic data from a full simulation of the Swarm mission, where it is found to significantly exceed all mandatory and most target accuracy requirements.",
author = "Sabaka, {T. J.} and Lars T{\o}ffner-Clausen and Nils Olsen",
year = "2013",
doi = "10.5047/eps.2013.09.007",
language = "English",
volume = "65",
pages = "1201--1222",
journal = "Earth, Planets and Space",
issn = "1343-8832",
publisher = "Terra Scientific Publishing Company",
number = "11",

}

Use of the Comprehensive Inversion method for Swarm satellite data analysis. / Sabaka, T. J.; Tøffner-Clausen, Lars; Olsen, Nils.

In: Earth Planets Space, Vol. 65, No. 11, 2013, p. 1201-1222.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Use of the Comprehensive Inversion method for Swarm satellite data analysis

AU - Sabaka, T. J.

AU - Tøffner-Clausen, Lars

AU - Olsen, Nils

PY - 2013

Y1 - 2013

N2 - An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agency (ESA). This new algorithm improves on a previously developed version in several ways, including the ability to process groundbased observatory data, estimation of rotations describing the alignment of vector magnetometer measurements with a known reference system, and the inclusion of ionospheric induction effects due to an a priori 3-dimensional conductivity model. However, the most substantial improvements entail the application of a mechanism termed “Selective Infinite Variance Weighting” (SIVW), which mitigates the effects of non-zero mean systematic noise and allows for the exploitation of gradient information from the low-altitude Swarm satellite pair to determine small-scale lithospheric fields, and an improvement in the treatment of attitude error due to noise in star-tracking systems over previously established methods. The advanced CI algorithm is validated by applying it to synthetic data from a full simulation of the Swarm mission, where it is found to significantly exceed all mandatory and most target accuracy requirements.

AB - An advanced algorithm, known as the “Comprehensive Inversion” (CI), is presented for the analysis of Swarm measurements to generate a consistent set of Level-2 data products to be delivered by the Swarm “Satellite Constellation Application and Research Facility” (SCARF) to the European Space Agency (ESA). This new algorithm improves on a previously developed version in several ways, including the ability to process groundbased observatory data, estimation of rotations describing the alignment of vector magnetometer measurements with a known reference system, and the inclusion of ionospheric induction effects due to an a priori 3-dimensional conductivity model. However, the most substantial improvements entail the application of a mechanism termed “Selective Infinite Variance Weighting” (SIVW), which mitigates the effects of non-zero mean systematic noise and allows for the exploitation of gradient information from the low-altitude Swarm satellite pair to determine small-scale lithospheric fields, and an improvement in the treatment of attitude error due to noise in star-tracking systems over previously established methods. The advanced CI algorithm is validated by applying it to synthetic data from a full simulation of the Swarm mission, where it is found to significantly exceed all mandatory and most target accuracy requirements.

U2 - 10.5047/eps.2013.09.007

DO - 10.5047/eps.2013.09.007

M3 - Journal article

VL - 65

SP - 1201

EP - 1222

JO - Earth, Planets and Space

JF - Earth, Planets and Space

SN - 1343-8832

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