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Record W2154561622 · doi:10.1186/1687-6180-2014-107

GPS-R L1 interference signal processing for soil moisture estimation: an experimental study

2014· article· en· W2154561622 on OpenAlexfundno aff
Songhua Yan, Zhengyong Li, Kegen Yu, Kefei Zhang

Bibliographic record

VenueEURASIP Journal on Advances in Signal Processing · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaAustralian Research CouncilAlzheimer Society Research Program
KeywordsGlobal Positioning SystemGPS signalsRemote sensingInterference (communication)Multipath propagationComputer scienceWater contentEnvironmental scienceSIGNAL (programming language)Multipath interferenceReflectometryAssisted GPSGeologyTelecommunications

Abstract

fetched live from OpenAlex

Global positioning system reflectometry (GPS-R) is an emerging area of GPS applications in microwave remote sensing using multipath reflected signals. Soil moisture estimation is one of the many potential applications of the GPS-R technique. The focus of this study is on investigating the feasibility of soil moisture estimation based on GPS L1 band interference signals which can be readily captured using a low-cost off-the-shelf L1-band GPS receiver. The theoretical background is studied, and the field experiments conducted are described. Power spectrum analysis is performed on the received interference signals to determine the interference signal frequency variation, and cosine similarity is applied to identify the initial phase change. Data collected at a number of continuously operating GPS stations are also analyzed. The results demonstrate that both interference signal frequency and phase have changed significantly after rainfalls occurred. That is, it is possible to estimate soil moisture by analyzing the frequency change and phase shift. However, it is also observed that the phase shift is inconsistent in some cases. Ongoing work will focus on figuring out the source of the inconsistency so that reliable estimation of soil moisture can be achieved.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.309
Teacher spread0.291 · 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.

Study designSimulation or modeling
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

Citations13
Published2014
Admission routes1
Has abstractyes

Explore more

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