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Record W2066886708 · doi:10.1109/spawc.2014.6941925

Joint TOA/AOA estimation of IR-UWB signals in the presence of multiuser interference

2014· article· en· W2066886708 on OpenAlex
Fang Shang, Benoı̂t Champagne, Ioannis Psaromiligkos

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsTime of arrivalAngle of arrivalEstimatorComputer scienceInterference (communication)Ultra-widebandDirection of arrivalAlgorithmJoint (building)Impulse (physics)Noise (video)Channel (broadcasting)Electronic engineeringAntenna (radio)TelecommunicationsStatisticsMathematicsPhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

We present a joint estimator of the time-of-arrival (TOA) and angle-of-arrival (AOA) for impulse radio ultra-wideband (IR-UWB) localization systems in which an antenna array is employed at the receiver and multiuser (MUI) interference exists. The proposed method includes 3 steps: (1) time-alignment and averaging to reduce the power level of the MUI and background noise; (2) preliminary TOA estimation based on energy detection followed by quadratic averaging; (3) joint TOA and AOA estimation using a recently proposed log likelihood function, but further extended to consider the effect of MUI. The validity of the proposed method is demonstrated by numerical simulations over a realistic space-time channel model.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.164

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 head0.019
GPT teacher head0.237
Teacher spread0.219 · 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

Quick stats

Citations11
Published2014
Admission routes1
Has abstractyes

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