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Record W2811413416 · doi:10.1109/tap.2018.2851291

Impact of Element Pattern Symmetry on the Effective Degrees of Freedom in Dual-Polarized GNSS Adaptive Antenna Arrays

2018· article· en· W2811413416 on OpenAlexaff
Navid Rezazadeh, L. Shafai

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2018
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGNSS applicationsDual (grammatical number)Antenna (radio)Degrees of freedom (physics and chemistry)Element (criminal law)PhysicsDirectional antennaComputer scienceAcousticsTelecommunicationsGlobal Positioning System

Abstract

fetched live from OpenAlex

The effect of element pattern symmetry on the performance of dual-polarized global navigation satellite system adaptive antenna arrays is investigated. To this end, using analytical expressions for the far-fields of circular microstrip antennas, the steady-state beamforming performance of a two-element dual-polarized array with three degrees of freedom (DOFs) is studied through many Monte Carlo simulations. It is shown that in the presence of randomly polarized interferers, regardless of the element pattern symmetry, the dual-polarized array can use all its DOF effectively to suppress up to three interferers and is as effective as a four-element right-handed circularly polarized (RHCP) array. It is, however, shown that if the interferers are RHCP, the dual-polarized array can use its DOF effectively only when the element patterns are asymmetric (unequal in E- and H-planes) and is ineffective in suppressing more than one interferer when the element patterns are symmetric (equal in E- and H-planes). This limitation is important in practice if the interferers are known to be RHCP and the array ground plane is small, since the patterns of microstrip antennas with small ground planes can become nearly symmetric. This finding is verified with a fabricated prototype of a two-element dual-polarized array with a small ground plane.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.499

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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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