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Record W2613185348 · doi:10.4236/pos.2017.81001

The CanX-7 Nanosatellite ADS-B Mission: A Preliminary Assessment

2017· article· en· W2613185348 on OpenAlexaffabout
Ron Vincent, Richard Van Der Pryt

Bibliographic record

VenuePositioning · 2017
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsPayload (computing)SatelliteRemote sensingAntenna (radio)RadarSecondary surveillance radarComputer scienceAutomatic dependent surveillance-broadcastCommunications satelliteOrbit (dynamics)Ground stationTelecommunicationsGeographyAerospace engineeringEngineeringAviation

Abstract

fetched live from OpenAlex

The development of space-based Automatic Dependent Surveillance-Broadcast (ADS-B) will allow surveillance of aircraft in areas not covered by radar or ground-based ADS-B systems. In September 2016, the Canadian Advanced Nanospace eXperiment-7 (CanX-7) satellite was launched into a 690 km sun synchronous orbit with an ADS-B receiver payload. The first phase of ADS-B data collection took place over the North Atlantic between 4 and 31 October. A preliminary assessment of the data indicates that the average ADS-B signal strength is close to the calculated receiver detection threshold of D94.5 ± 0.5 dBm. The pattern of received ADS-B reception appears to be consistent with a signal propagation model developed for the CanX-7 mission. Future work includes the comparison of coincidental flight plan data for the operations area and an analysis of the payload antenna pattern.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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 designNot applicable
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

Citations16
Published2017
Admission routes2
Has abstractyes

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