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Record W2111895196 · doi:10.1109/ut.1998.670110

Implementation of adaptive processing in integrated active-passive sonars deploying cylindrical arrays

2002· article· en· W2111895196 on OpenAlexaff
Stergios Stergiopoulos, Amar Dhanantwari, J.J. Grodski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsWestern University
Fundersnot available
KeywordsSonarBeamformingAdaptive beamformerMarine mammals and sonarRemotely operated underwater vehicleUnderwaterRoboticsSynthetic aperture sonarComputer scienceReverberationRemotely operated vehicleSonar signal processingArray processingArtificial intelligenceEngineeringAcousticsSignal processingRobotMobile robotComputer hardwareTelecommunicationsGeologyElectrical engineeringAerospace engineeringDigital signal processingPhysics

Abstract

fetched live from OpenAlex

This paper presents the definition of a remotely operated vehicle (ROV) deploying a cylindrical array sonar for underwater robotics operations, such as mine-hunting. The various aspects of robotics arrangements for the ROV are discussed in association with the integrated functionality of the cylindrical array sonar including an adaptive beamformer. The proposed adaptive processing concept has been implemented in an integrated active-passive real-time sonar deploying a cylindrical array. Real data results from the adaptive and conventional beamforming outputs of the cylindrical array sonar system demonstrate the superior performance of the adaptive beamformer in suppressing the reverberation and cluttering effects in active sonar applications. Moreover, for passive sonar applications, the adaptive processing provides substantially improved angular resolution performance as compared with that of the conventional beamformer.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.435

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 communication0.0000.001
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 head0.031
GPT teacher head0.281
Teacher spread0.250 · 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 designOther design
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

Citations5
Published2002
Admission routes1
Has abstractyes

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