MétaCan
Menu
Back to cohort

3-D Pseudo-Noise Interferometry for a Novel Bistatic Aperture Lidar

2025· article· en· W4413158252 on OpenAlexaff
Kai-Ting Ting, Kelvin Wagner, Charles G. Garvin, Philip Gatt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsBistatic radarInterferometryLidarSynthetic aperture radarRemote sensingNoise (video)Computer scienceOpticsGeologyRadar imagingPhysicsTelecommunicationsArtificial intelligenceRadarImage (mathematics)

Abstract

fetched live from OpenAlex

We reported an unconventional coherent Pseudo-Noise (PN) interferometry with true 3-D lidar imaging capability by recording multiple fast-time acquisition for parallel 2-D ranging while achieving azimuth compression for the third dimension without using a filled aperture. Two transmitters broadcast the same but mutually time-delayed Binary Phase Shift Keyed (BPSK) PN-code riding on shifted RF carrier frequencies to track the quadratic phase trajectory of the target in azimuth using synthetic wavelength. The range/cross-range is obtained while two time-delayed backscattered BPSK signals interfere at the receiver through code-multiplexing of the interferometric PN-modulation that encodes time-difference-of-arrival (TDOA) and time-of-flight (TOF) delay in parallel using the shift-and-add property of the maximum-length (ML) sequences. The simulation and proof-of-concept experiment demonstrate synthetic aperture (SA) imaging in azimuth dimension in addition to the 2-D parallel ranging from the PN interferometry.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score0.436

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 science0.0010.000
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 head0.297
Teacher spread0.266 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicOptical measurement and interference techniquesFrench-language works237,207