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Record W1965582438 · doi:10.1109/icassp.2010.5496261

Cramér-Rao bound for time reversal active array direction of arrival estimators in multipath environments

2010· article· en· W1965582438 on OpenAlex

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
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsMultipath propagationEstimatorCramér–Rao boundDirection of arrivalAlgorithmComputer scienceFinite-difference time-domain methodGround-penetrating radarRadarUpper and lower boundsRange (aeronautics)Angle of arrivalDelay spreadAcousticsElectronic engineeringEstimation theoryMathematicsPhysicsEngineeringTelecommunicationsStatisticsMathematical analysisAntenna (radio)Optics

Abstract

fetched live from OpenAlex

In this paper, we study the Cramér-Rao bound (CRB) for time reversal (TR) based direction of arrival (DOA) estimators operating in a rich multipath environment. Our setup is based on an array of active antennas capable of estimating the range and DOA of a passive target. We derive an analytical expression for the CRB of the TR/DOA estimator and compare it with that of the conventional DOA estimator by expressing the two CRBs in terms of the multipath parameters (multipath's attenuations and delays). Our analytical results are verified by running Ground Penetrating Radar (GPR) simulations using the electromagnetic Finite Difference Time Domain (FDTD) models. Our simulations illustrate the potential of superior performance with gains of up to 15 dB possible with the TR/DOA estimator over the conventional approach.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.610

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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
Published2010
Admission routes1
Has abstractyes

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