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Record W1534252773 · doi:10.1109/iscas.2015.7169106

Real-Valued ESPRIT for two-dimensional DOA estimation of noncircular signals for acoustic vector sensor array

2015· article· en· W1534252773 on OpenAlexaff
Han Chen, Wei‐Ping Zhu, M.N.S. Swamy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsAzimuthDirection of arrivalComputational complexity theoryAlgorithmComputer scienceMatching (statistics)Sensor arrayCramér–Rao boundEstimation theoryMathematicsTelecommunicationsStatistics

Abstract

fetched live from OpenAlex

In this paper, we propose a real-valued ESPRIT algorithm for two-dimensional direction of arrival (2D DOA) estimation of noncircular signals using arbitrarily spaced acoustic vector sensor array. By utilizing the noncircularity of the signals, the proposed algorithm provides a better estimation performance while having only slightly larger computational complexity as compared to the traditional complex ESPRIT algorithm. Furthermore, the proposed algorithm gives automatically paired azimuth and elevation angle estimates without requiring extra pair matching. Simulation results are presented to demonstrate the estimation performance of the proposed algorithm as compared to the traditional ESPRIT algorithm as well as Cramer-Rao bound (CRB).

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.374
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.037
GPT teacher head0.319
Teacher spread0.282 · 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
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

Citations5
Published2015
Admission routes1
Has abstractyes

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