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Record W4288070411 · doi:10.18280/ts.390321

Approximate Position Estimation Method of Weak-Signal Receiver of Global Navigation Satellite Systems Assisted by Barometric Altimeter

2022· article· en· W4288070411 on OpenAlexvenueno aff
Peng Wu, Feng Lu, Haibo Tong, Zhuxian Zhang

Bibliographic record

VenueTraitement du signal · 2022
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsGNSS applicationsGlobal Positioning SystemComputer sciencePosition (finance)Frame (networking)AltimeterSynchronization (alternating current)SatelliteElevation (ballistics)SIGNAL (programming language)Frame synchronizationReal-time computingPrecise Point PositioningSatellite navigationSatellite systemReference frameRemote sensingGeodesyGeographyTelecommunicationsMathematicsEngineering

Abstract

fetched live from OpenAlex

The satellite navigation receiver works in an environment, where the received signal is very weak. Sometimes, frame synchronization is impossible, for the antenna rotates with the flight carrier, and occlusions exist in the environment. After losing look, it is necessary to positioning reacquired signals. Rapid positioning can be completed without frame synchronization, utilizing auxiliary positioning algorithms like A-GPS. If the carrier is highly dynamic, however, the computing load of reacquired signal positioning would be too high, owing to the extreme fuzziness of the approximate position. Therefore, the application of auxiliary positioning algorithms is premised on the acquisition of the approximate position information, when frame synchronization is not possible. This paper proposes a method for estimating the approximate position of a satellite navigation receiver without frame synchronization: The approximate position is quickly obtained by measuring the elevation with a barometer, and searching under a user-defined “geocenter-satellite” coordinate system. Simulation results show that, the proposed algorithm could successfully compute the approximate position, when the barometric altimeter measures elevation with an accuracy within 1.8km, and when the coordinate system is established based on satellites with a long distance and a low angle of elevation, under the condition of global navigation satellite system (GNSS) constellation.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

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