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Record W4408990239 · doi:10.3390/engproc2025088022

Combined Navigation and Tracking with Applications to Low Earth Orbit Satellites

2025· article· en· W4408990239 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsTracking (education)Computer scienceLow earth orbitSatellite trackingOrbit (dynamics)Earth's orbitGeocentric orbitMedium Earth orbitRemote sensingEarth observationAerospace engineeringSatelliteGeodesyAstrobiologyGeologyEngineeringPhysicsSpacecraft

Abstract

fetched live from OpenAlex

Low Earth Orbit (LEO) satellites complement classic GNSS by offering stronger signals, improved visibility, and system redundancy. Typical high speeds in LEO orbits generate rapid variations of the receiver-to-satellite geometry, which can improve the convergence of Precise Point Positioning (PPP) algorithms. However, high dynamics also induce strong Doppler rates at the receiver, which make the tracking procedures more difficult. In this paper, a loosely combined navigation and tracking architecture is applied to a Xona PULSAR™ Demonstration Signal in the L-Band such that the dynamic stress perceived by the receiver is mitigated. Other practical aspects of the Xona PULSAR™ receiver will be also discussed.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.201

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 head0.003
GPT teacher head0.195
Teacher spread0.192 · 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

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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