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Record W1966529494 · doi:10.1364/ol.37.000755

Photonic approach to the measurement of time-difference-of-arrival and angle-of-arrival of a microwave signal

2012· article· en· W1966529494 on OpenAlexaff
Xihua Zou, Wangzhe Li, Wei Pan, Bin Luo, Lianshan Yan, Jianping Yao

Bibliographic record

VenueOptics Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsOpticsAngle of arrivalArrival timeMicrowaveSIGNAL (programming language)Time of arrivalSignal processingPhysicsPhotonicsComputer scienceTelecommunicationsRadarEngineering

Abstract

fetched live from OpenAlex

We propose and experimentally demonstrate a photonic approach to the measurement of the time-difference-of-arrival (TDOA) and the angle-of-arrival (AOA) of a microwave signal. In the proposed system, the TDOA and the AOA are equivalently converted into a phase shift between two replicas of a microwave signal received at two cascaded modulators. The light wave from a CW laser is externally modulated by the microwave signal at the first modulator, which is biased to suppress the optical carrier, leading to the generation of two first-order sidebands, which are further modulated by the phase-delayed microwave signal at the second modulator. Two optical components at the carrier wavelength are generated. The total power at the carrier wavelength is a function of the phase shift due to the coherent interference between the two components. Thus, by measuring the optical power, the phase shift is estimated. The AOA is calculated from the measured phase shifts. In our experiment, the phase shift of a microwave signal at 18 GHz from -160° to 40° is measured with measurement errors of less than ±2.5°.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations76
Published2012
Admission routes1
Has abstractyes

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