Determination of chip rate and center frequency for a spread spectrum acoustic ranging system
Bibliographic record
Abstract
Spread spectrum systems are commonly used for ranging. Perhaps the most pervasive system is GPS. Because such a system relies on a high frequency signal, the receiver must have an unobstructed view of the sky. There are situations in which one cannot use GPS, such as in an orchard or indoors. This paper suggests that ranging can be achieved by applying the spread spectrum technique to sound waves rather than RF. In using air as the medium, there are many different factors that must be considered in deciding what the appropriate chip rate and center frequency should be. The speed of sound is much slower than RF. It changes significantly with a change in temperature. There are Doppler shift effects. The available bandwidth relative to center frequency is enormous when compared to RF. The attenuation of the higher frequencies is very dramatic for sound. This paper considers these factors and others in determining an appropriate chip rate and center frequency for acoustic ranging. Low frequencies in sound are attenuated much less than high frequency signals and to capitalize on this it was found that a center frequency of zero hertz and a relatively low chip rate of 100 chips/sec would be suitable.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".