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Record W4410404727 · doi:10.1121/10.0036691

Derivation of a Low-Complexity-Pilot-Aided Doppler estimator for underwater acoustic applications

2025· article· en· W4410404727 on OpenAlexaff
Ali M. Bassam, Mae Seto

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEstimatorCramér–Rao boundDoppler effectComputer scienceChannel (broadcasting)AlgorithmMinimum mean square errorMultiplexingMean squared errorCover (algebra)Underwater acousticsSignal processingMathematicsUnderwaterTelecommunicationsStatisticsEngineeringRadar

Abstract

fetched live from OpenAlex

A time-domain Doppler estimation method is developed using shift-orthogonal pilot sequences in underwater acoustic (UWA) orthogonal frequency division multiplexing systems. The derivation uses channel assumptions that cover a wide class of UWA communication environments. The proposed estimator is computationally lightweight, targeting applications with limited on-board processing power. Asymptotic analysis for high signal-to-noise ratios and a Cramer-Rao lower bound are presented. Although it is sub-optimal and is outperformed by some estimators, the proposed estimator outperforms many existing estimators found in the literature (in terms of mean square error).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.270

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 science0.0010.000
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 head0.024
GPT teacher head0.263
Teacher spread0.239 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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