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Record W2162287492 · doi:10.1109/vetecf.2008.71

Zero-Knowledge Beamforming for Mobile Satellite Phased Array Antenna

2008· article· en· W2162287492 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
TopicAntenna Design and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhase shift modulePhased arrayBeamformingComputer scienceAntenna arrayAntenna (radio)Electronic engineeringA priori and a posterioriPhased-array opticsPhase (matter)Convergence (economics)Power (physics)AlgorithmControl theory (sociology)EngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

In this paper, we introduce a novel beamforming algorithm for single receiver phased array antenna systems and study its performance in terms of the convergence speed and the steady state error, through simulations and experimental tests. Neither a priori knowledge of the target's direction, nor the phase-voltage characteristic of the phase shifters are required in this algorithm. Instead, the total received power, which is the only array output, is sampled to perform the beamforming and adjust the phase shifters. Insensitivity to the variation of the phase shifter characteristics, and simultaneous calibration is an important feature of this algorithm. This algorithm has been successfully applied to a 16-element Ku-band phased array.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.468

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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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