The designing of an indoor acoustic ranging system using the audible spread spectrum LFM (CHIRP) signal
Bibliographic record
Abstract
This paper presents an audible spread spectrum (SS) acoustic ranging system for indoor applications. RF synchronization along with using wideband audible signal results in significant reduction in error and reduces the cost and complexity of the ranging hardware and removes the need for high sampling rates. The SS signal, which in this case, is a linear frequency modulated (LFM) pulse (chirp), emanates from a speaker and is received by a microphone. It is then correlated with a delayed copy of the same signal through a matched filter. Important issues of acoustic propagation, along with the impact of indoor reverberation on time of arrival (TOA) estimation are taken into account to use an appropriate LFM pulse. It is found that, an LFM pulse with 3 kHz bandwidth, center frequency of 2 kHz, and chirp rate of 60 Hz/ms would have good performance in range accuracy
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".