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Record W2541347770 · doi:10.1109/acssc.2012.6489236

Transmit beamspace design for direction finding in colocated MIMO radarwith arbitrary receive array and even number of waveforms

2012· article· en· W2541347770 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
TopicRadar Systems and Signal Processing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMIMOComputer scienceWaveformAlgorithmAntenna arrayRadarAntenna (radio)Matrix (chemical analysis)Rotational invarianceDirection of arrivalElectronic engineeringTelecommunicationsEngineeringBeamforming

Abstract

fetched live from OpenAlex

In this paper, colocated multiple-inputmultiple-output (MIMO) radar is used for direction-of-arrival (DOA) estimation. The case of even but otherwise arbitrary number of transmit waveforms is considered. In order to obtain a virtual array with a large number of virtual antenna elements and at the same time obtain a significant signal-to-noise ratio (SNR) gain, a proper transmit beamspace is designed. Moreover, to allow for simple DOA estimation algorithms at the receive array, it is shown that the rotational invariance property (RIP) for the virtual array can be guaranteed at the transmit array also by a proper beamspace design. The main idea of such beamspace design is to obtain the RIP by imposing a specific structure on the beamspace matrix and then designing the matrix to obtain a desired beampattern and a uniform power distribution across antenna elements. Simulation results demonstrate the advantages of the proposed DOA estimation method based on colocated MIMO radar with beamspace design.

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 score0.382
Threshold uncertainty score0.383

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 head0.240
Teacher spread0.221 · 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

Citations15
Published2012
Admission routes1
Has abstractyes

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