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Record W2804130399 · doi:10.1109/lcomm.2018.2837913

Multistatic Radar Placement Optimization for Cooperative Radar-Communication Systems

2018· article· en· W2804130399 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

VenueIEEE Communications Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer scienceRadarBistatic radarMultistatic radarRadar engineering detailsInterference (communication)Radar lock-onContinuous-wave radarMan-portable radarLow probability of intercept radarReal-time computingElectronic engineeringChannel (broadcasting)TelecommunicationsRadar imagingEngineering

Abstract

fetched live from OpenAlex

In this letter, we investigate a scenario where both multistatic radar and point-to-point communication systems are present with a partial or total spectrum-sharing constraint. We propose a new adaptive radar receivers placement mechanism that jointly maximizes the signal-to-interference-plus noise ratio of each communication transmitter-radar receiver channel while minimizing the geometric dilution of precision. The proposed joint approach performs well in the presence of communication interference on the radar side. In fact, the proposed approach helps to increase the capability to properly demodulate the communication data at each radar receiver resulting in the less radar measurement errors due to communication interference while enhancing the target positioning accuracy.

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: Methods · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.788

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 studies0.0010.000
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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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