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Record W4378672616 · doi:10.24425/agg.2022.141916

The positioning performance of low-cost GNSS receivers in the Precise Point Positioning method

2022· article· en· W4378672616 on OpenAlexfundaboutno aff
Mustafa Fahri Karabulut, Nedim Onur Aykut, Burak Akpınar, Güldane Oku Topal, Zübeyir Bilal ÇAKMAK, Bilge Doran, Ahmet Anıl Dindar, Cemal Özer Yiğit, Mert Bezcioğlu, Anıl Zafer

Bibliographic record

VenueAdvances in Geodesy and Geoinformation · 2022
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
FundersNatural Resources CanadaYildiz Teknik Üniversitesi
KeywordsPrecise Point PositioningGNSS applicationsHybrid positioning systemComputer sciencePoint (geometry)Global Positioning SystemPositioning systemTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Satellite-based positioning, which started being developed in the mid-1960s for military purposes, is now used in almost every area. For the studies single and/or double frequency receivers are used. The cost of a receiver and antenna couple that have capable of high coordinate accuracies ranges from $3000 to $15000. With the production of Original Equipment Manufacturer (OEM) receivers, the cost of satellite-based location determination decreases to approximately one in 10 for the civilian user compared to the operations performed with geodetic receivers and antennas. However, although these receivers collect data in multi-Global Navigation Satellite System (GNSS) and frequencies, the accuracy of the coordinate values estimated is not as high as geodetic receivers and antennas. Therefore, it is necessary to carry out an accuracy study to obtain information about which studies can be used in. In this study, measurements were made at the UZEL point located on the roof of the Yıldız Technical University Geomatics Engineering Department by using the ZED-F9P-02B OEM multi GNSS receiver and ANN-MB L1/L2 multi-band GNSS patch antenna. The performance of the test results has been examined by comparing the results from CSRS(Canadian Spatial Reference System)-PPP with the coordinates of the UZEL point. As a result of the comparison, the difference between the coordinate determined with collected 3.5 hr data and the coordinates of the UZEL point has been determined as – 1.4 cm, 2.8 cm, and 9.3 cm in the East, North, and Height directions, respectively

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.003
GPT teacher head0.223
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2022
Admission routes2
Has abstractyes

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