Self-organized synchronization based on a chirp-sequence waveform for an HF ocean radar network
Why this work is in the frame
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Bibliographic record
Abstract
HFocean radars are usually installed along the coast and deliver remote sensing information by transmitting a radio signal with an operating frequency between 3 and 30 M1z. The frequency band allows for a large coverage of ocean surface that could extend more than 200 kilometers offshore depending on the transmit frequency and other operating conditions. To provide a dense coverage of the sea surface, the installation of ocean radars in a radar network may require that the transmitting and receiving units of a radar network demand time synchronization between the units to perform correct space-time measurements of ocean parameters. In this paper, a selforganized synchronization for 1W ocean radars is considered without the use of Global Positioning System (GPS) devices. In the case of multiple transmitters, the power peaks are observed in spectra simultaneously for each of the transmitters; hence the time shift can be estimated separately for each of them. The selforganized approach is very useful for the case of multiple transmitters and receivers in a radar network as well as in multiple-input-multiple-output (MIMO) radar configurations, which utilize the feasibility of occupying less space for a 1W radar receive antenna while maintaining the high spatial resolution of the radar data.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it