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Optimized Parallel and Serial Array Antenna Design for X-Band Aviation Radar Sensors

2024· article· en· W4408048416 on OpenAlexaff
Kavita Avinash Patil, A.B. Gurulakshmi, P S Neethu, Salna Joy, Nanditha Krishna, R Baby Chithra, N J Avinash

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsRadarComputer scienceX bandAntenna (radio)AviationSensor arrayRadar engineering detailsElectronic engineeringElectrical engineeringEngineeringTelecommunicationsAerospace engineeringRadar imaging

Abstract

fetched live from OpenAlex

This paper aims to devise an antenna structure tailored for seamless integration into aviation radar sensors. The primary design objectives entail the creation of an antenna resonating within the X-band frequency range, spanning from 8 GHz to 12 GHz, with a central frequency of 9.79 GHz, while prioritizing portability. A meticulously dimensioned unit cell is engineered to achieve these specifications, resulting in an antenna design operating at 10.36 GHz. Key parameters including S11, Gain, Efficiency, and Radiation characteristics are meticulously assessed. Subsequently, these unit cells are arranged in serial and parallel configurations and analyzed across various metrics. Noteworthy findings reveal that the parallel array design exhibits superior radiation performance at 10.3 GHz. In contrast, the serial array configuration demonstrates enhanced attributes, including higher gain and improved S-parameter characteristics, particularly at 10.8 GHz. The input impedances were readily adjusted to match 50-ohm feedlines. The antenna design leverages dielectric materials such as Duriod for the substrate and copper for the patch and ground components. Specifically, the Duriod substrate boasts a dielectric coefficient of 2.2, with a substrate thickness of 1.57 and a copper thickness of ${0. 0 3 5}$. This investigation underscores the efficacy of the serial array antenna design, highlighting its potential for optimal performance in aviation radar sensor applications..

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.435
Threshold uncertainty score0.446

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 head0.016
GPT teacher head0.218
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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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