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Record W3019597002 · doi:10.1109/taes.2020.2988424

DOA Elevation and Azimuth Angles Estimation of GPS Jamming Signals Using Fast Orthogonal Search

2020· article· en· W3019597002 on OpenAlex
Abdalla Osman, Mohamed M. Moussa, Mohamed Tamazin, Michael J. Korenberg, Aboelmagd Noureldin

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

VenueIEEE Transactions on Aerospace and Electronic Systems · 2020
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsQueen's UniversityRoyal Military College of Canada
Fundersnot available
KeywordsJammingAzimuthDirection of arrivalInterference (communication)Global Positioning SystemComputer scienceGPS signalsElevation (ballistics)SIGNAL (programming language)TelecommunicationsAssisted GPSEngineeringMathematicsAntenna (radio)Physics

Abstract

fetched live from OpenAlex

This article introduces a new two-dimensional direction of arrival (DOA) elevation and azimuth angles estimation technique for global positioning system (GPS) jamming signals in challenging environments based on the fast orthogonal search (FOS) method. FOS-DOA estimation is accommodated to process array structure optimized for interference rejection. Performance of FOS-DOA is compared to the predominant multiple signal classification (MUSIC) DOA estimation method. Results showed significant improvement in jamming detection of the multiple sources of interference with slight variations in their amplitude at jamming to signal ratio (JSR) 15 and 45 dB. The improvement introduced by the proposed DOA estimation technique is mainly in the accuracy of detecting the number of jammers and their DOA.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.699
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.268
Teacher spread0.242 · 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