MétaCan
Menu
Back to cohort
Record W4321996204 · doi:10.5194/egusphere-egu23-10423

A matched filter approach for the calibration of GRACE and GRACE-FO accelerometers.

2023· preprint· en· W4321996204 on OpenAlexaff
Spiros Pagiatakis, Myrto Tzamali

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsYork University
Fundersnot available
KeywordsAccelerometerSIGNAL (programming language)CalibrationFilter (signal processing)Gravitational fieldNoise (video)Gravitational accelerationComputer scienceSatelliteAccelerationGeodesyGlobal Positioning SystemGravimeterGPS signalsRadarRemote sensingPhysicsAssisted GPSGeologyOpticsTelecommunicationsArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

For the accurate determination of the gravity field of the Earth, the accelerometers on board GRACE and GRACE-FO missions need to be calibrated, which is a rather challenging task. In many gravitational field studies, the bias and scale factors are introduced, among others, as unknown parameters in the gravity field recovery process and are estimated concurrently with the gravity field parameters. In other studies, the calibration method makes use of modeled accelerometer data, and the parameters are estimated in a least squares adjustment.  Depending on the calibration process, the scale factors and biases may vary significantly. In this study, an alternative calibration method is followed using the matched filter method. This method is widely used in radar applications for scattered signal detection purposes since it maximizes the signal-to-noise ratio. The idea behind this method is that a known signal is transmitted out and the reflected signal is compared to the known transmitted signal. This allows the proposed method to be based only on the satellite measurements.  In this study, the total accelerations of the satellite derived from the GPS positions, play the role of the transmitted signal that contains both the gravitational and the non-gravitational accelerations. The penumbra transitions, which appear as jumps (offsets) of very short duration in the accelerometer measurements, are used as the known calibration pulses that need to be detected in the transmitted signal. The process of matching (focusing) the penumbra transition pulse on the GPS accelerations is presented step by step and as a result, 30 daily scale factors are calculated for both missions during different periods of solar activity. The biases of the instrument are calculated daily using a second order polynomial fit. The scale factor and the biases appear to be correlated with the β’ angle variations (the angle that indicates when the satellite is in a full sun orbit). The scale factors of the cross-track component in both missions show the largest variations, since the y-axis of the accelerometer is the least sensitive, while the scale factors in the x-axis show the largest sensitivity due to thermal variations in the atmosphere . The performance of the calibration parameters during high and low solar activity is examined and evaluated.  

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.255
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicGeophysics and Gravity MeasurementsFrench-language works237,207