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Record W1583390499 · doi:10.1109/milcom.2002.1180434

Enhancing multiple-aperture Ka-band Navy SATCOM antennas with electronic tracking and reflectarrays

2003· article· en· W1583390499 on OpenAlexafffund
E.B. Felstead, J. Shaker, M. R. Chaharmir, A. Petosa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsCommunications Research Centre Canada
FundersMinistère de la Défense NationaleDefence Research and Development Canada
KeywordsTelecommunications linkAperture (computer memory)Ka bandAntenna (radio)Side lobeEngineeringPolarization (electrochemistry)Computer scienceElectronic engineeringOpticsAcousticsElectrical engineeringPhysicsTelecommunications

Abstract

fetched live from OpenAlex

In naval SATCOM applications, there are advantages to using multiple antenna panels, each of limited scan range covering only a portion of the required hemisphere. For mechanical steering, the depth of each panel can be reduced by dividing the required aperture into multiple, smaller, sub-apertures at the cost of needing coherent combining. Two enhancements to multiple sub-aperture systems are presented. First, a method, akin to radar monopulse tracking techniques, is introduced that uses the multiple sub-beams for fine acquisition and tracking of the downlink signal. The individual sub-beams are steered to point slightly off center. A portion of the downlink signal from each beam is tapped off, detected, and used in an algorithm to compute the pointing error of the combined antenna beam center. This error estimate is used in a feedback loop to track the downlink signal. In the second enhancement, the sub-aperture antennas are implemented using reflectarray reflectors. Printed reflectarrays are used in place of conventional parabolic dishes. To minimize the design complexity of the feeds, the reflectarray elements are designed to transform the linear polarization from the feeds to circular polarization. The reflectarray design is capable of handling both right-hand and left-hand circular polarization. Furthermore, the reflectarray is designed with separate focal points for the transmit and receive signals. This removes the need for an orthomode transducer and for diplexers, resulting in considerable cost and weight savings. A Ka-band implementation is described.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.723

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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 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

Citations1
Published2003
Admission routes2
Has abstractyes

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