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Record W2735283278 · doi:10.5515/kjkiees.2017.28.5.419

A CMOS UWB RFIC Based Radar System for High Speed Target Detection

2017· article· en· W2735283278 on OpenAlexaff
Sang Gyun Kim, Yun Seong Eo, Hyung Chul Park

Bibliographic record

VenueThe Journal of Korean Institute of Electromagnetic Engineering and Science · 2017
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsCanadian Meteorological and Oceanographic Society
FundersKorea Evaluation Institute of Industrial TechnologySeoul National University of Science and Technology
KeywordsRFICCMOSRadarBandwidth (computing)Electronic engineeringChipRadar systemsEnvelope detectorElectrical engineeringComputer scienceEngineeringTelecommunicationsAmplifier

Abstract

fetched live from OpenAlex

This paper presents CMOS UWB RFIC based radar system for high speed target detection. The system can achieve resolution of 15 cm and detection range of 15 m. For developed system, single chip CMOS UWB IC is implemented. To reduce the measuring and processing time, envelope detection and equivalent time sampling technique are used. Measurement results show that the bandwidth and center frequency of UWB pulse can be adjusted in the range of 0.5 GHz∼1.0 GHz, 3.5 GHz∼4.5 GHz, respectively. Signal processing time including scan time over 15 m distance is about 150 μsec.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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