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Record W3047033669 · doi:10.1029/2019rs007027

Transmit Beamforming for Phased Array Based on Constrained Wind‐Driven Optimization Method

2020· article· en· W3047033669 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

VenueRadio Science · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsUniversity of Calgary
FundersInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsBeamformingOptimization problemPhased arrayComputer scienceMathematical optimizationNull (SQL)RadarConstraint (computer-aided design)Reduction (mathematics)Control theory (sociology)Constrained optimizationTransmitter power outputPower (physics)MathematicsAntenna (radio)TelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Abstract In this paper, we present a novel improved wind‐driven optimization (IWDO) for transmit beamforming of phased array radar, which is assumed as a multiple constraints optimization problem. First, the emitted signal model and objective functions of optimization with constraints are presented. Second, all air parcels are divided into feasible and infeasible parcels, and then the target function and constraint violation of air parcels are evaluated. Finally, the constrained optimization problem is converted into the nonconstraint problem, and the proposed modified wind‐driven optimization (WDO) has been applied for the optimal design of beamforming with null steering. The simulation results show that the proposed method outperforms conventional optimization methods in the optimal beamforming by achieving more reduction in the null steering and obtaining accurate peak power.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.407
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.247
Teacher spread0.228 · 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