Impact of bandwidth on antenna‐array noise matching
Bibliographic record
Abstract
Abstract This letter expands the treatments of wideband noise analysis of antenna arrays by including bandwidth effects on beam‐equivalent receiver noise temperature, , and the active reflection coefficient, . The particular focus of the letter is on receiver noise decorrelation in wideband systems having noise bandwidth 1 Hz. The new analysis and simulations show increase in and the departure of from that obtained using contemporary analyses for 1 Hz. Although the paper also shows that for many applications over moderate bandwidths and close connection between the receiver and array the influence of on is not significant, the simulations of a 71‐element array demonstrate that the noise decorrelation due to wide can result in tens of percent (as much as 45.5% in simulations described in this letter) increase in above the low‐noise amplifier minimum noise temperature, which should be taken into account at the design stage of ultra‐wide band systems, such as those under investigation by, for example, the Defense Advanced Research Project Agency (DARPA) in its wideband adaptive RF protection (WARP) program and ultra‐sensitive active electronically scanned array (AESA) radars for tracking stealth objects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".