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Millimeter Wave Microstrip Antennas for Radar Applications in the Ka-Band

2023· book-chapter· en· W4317759475 on OpenAlexaff
Salaheddine Aourik, Ahmed Errkik, Jamal Zbitou, Rachid Mandry, Ahmed Lakhssassi

Bibliographic record

VenueAdvances in mechatronics and mechanical engineering (AMME) book series · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsMicrostrip antennaCoaxial antennaAntenna measurementAntenna (radio)Electronic engineeringOmnidirectional antennaPatch antennaRadarAcousticsComputer scienceEngineeringTelecommunicationsElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

This chapiter starts with a general definition of the antennas. The next parts will talk about a microstrip antenna from the side of the double band in order to get an antenna that can do both reception and emission as well as developing the azimuth and angular resolution. This chapter has also introduced an antenna that separates the feeding part from the rayonnant one in an effective way that can enable us to develop the abilities of the radar antenna. Besides, it would also cope with the mechanic relation of the antenna. Another work has been presented to make electronic scanning more effective and faster. This would allow us to get rid of mechanic circulation by using butler matrix. Developing the antenna from the angular resolution has also been presented through widening the bandwidth by DGS technique and widening the reach via using the antenna array. Among the biggest problems are the surface waves and mutual coupling that present significant challenges to the designer because of their graduation of the antenna performance especially in the radar system.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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