A Method for Estimating the Spatial Coherence of Mid‐Latitude Skywave Propagation Based on Transionospheric Scintillations at 35 MHz
Bibliographic record
Abstract
Abstract The results of a study aimed at assessing the utility of transionospheric 35 MHz scintillation measurements toward cosmic radio sources for estimating the level of spatial coherence in high frequency (HF) skywave systems are presented. An array of four antennas in southern Maryland called the Deployable Low‐band Ionosphere and Transient Experiment was used. Two of the antennas within a ∼350‐m north/south baseline were used to monitor 35‐MHz intensity variations of two bright cosmic sources, Cygnus A and Cassiopeia A. The other two antennas, which were within a ∼420‐m east/west baseline, recorded the 7.85 MHz skywave from the CHU radio station near Ottawa, Ontario. These HF measurements were used to quantify the level of spatial coherence by measuring the amplitudes of the cross correlation of the two antennas' recorded voltages relative to the received power, which were typically ∼0.5 to 0.9, but occasionally near zero. An approximate scaling method was developed to estimate the expected cross‐correlation amplitude based on the 35‐MHz scintillations. This method assumes a single layer of irregularities at the reflection height that affects relatively small changes in electron density, the latter of which is generally appropriate for mid‐latitudes. It also assumes that the irregularity distribution follows that of the background electron density. These calculations typically captured the day‐to‐day variations in spatial coherence well (correlation coefficient r ≃ 0.6) while only marginally reproducing hour‐to‐hour variations (r ≃ 0.2). Thus, this method holds promise as an economical and passive means to assess the spatial coherence expected for skywave propagation within a given mid‐latitude region.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".