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Record W2421965999 · doi:10.1109/radar.2016.7485243

Reduced time-on-target in pulse Doppler radar: Slow time domain compressed sensing

2016· article· en· W2421965999 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSparse and Compressive Sensing Techniques
Canadian institutionsnot available
FundersAzrieli FoundationEuropean Commission
KeywordsComputer scienceNyquist rateDoppler effectPulse-Doppler radarTime domainRadarBandwidth (computing)Nyquist–Shannon sampling theoremDoppler radarContinuous-wave radarSIGNAL (programming language)Compressed sensingElectronic engineeringSampling (signal processing)Pulse repetition frequencyReal-time computingRadar imagingAlgorithmTelecommunicationsPhysicsFilter (signal processing)Computer visionEngineering

Abstract

fetched live from OpenAlex

Pulse Doppler radars measure both the targets distance to the transceiver and their radial velocity, through estimation of time delays and Doppler frequencies, respectively. This digital processing is traditionally performed on samples of the received signal at its Nyquist rate, which can be prohibitively high. Overcoming the rate bottleneck, sub-Nyquist sampling methods have been proposed that break the link between radar signal bandwidth and sampling rate. In this work, we extend this concept to the slow time domain. We choose to transmit non-uniformly spaced pulses in one direction, thus allowing to reduce the average time-on-target by exploiting the complementary set of transmitted pulses in another direction. Both software and hardware simulations demonstrate reduced time-on-target and recovery of several delay-Doppler maps within the same coherent processing interval.

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 score0.113
Threshold uncertainty score0.872

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)0.0010.001

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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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