Photonic-assisted multi-functional system for simultaneous distance, velocity and frequency measurement
Bibliographic record
Abstract
A photonic-assisted multi-functional system that can implement simultaneous distance, velocity and frequency measurement is proposed and experimentally demonstrated. The distance and the radial velocity of a moving target are measured by transmitting a complementarily (V-shaped) linear-frequency-modulated microwave waveform, and by mixing the reflected microwave waveform with the transmitted microwave waveform, two de-chirped waveforms with different carrier frequencies are generated. The distance and the radial velocity are measured by analyzing the de-chirped microwave waveforms. Frequency measurement can also be performed by the system which is done by modulating a received unknown signal on an optical carrier which is mixed with a frequency-sweeping light. By passing the mixed signal through an electrical bandpass filter, short electrical pulses are generated. By measuring the time delay difference between adjacent pulses, the frequency of the unknown signal is measured. The operation of the proposed system is evaluated experimentally. The results show that the distance and velocity can be measured with mean absolute errors of 2.95 cm and 6.09 cm/s, respectively, with a range resolution better than 5.5 cm. The frequency measurement function with the capability of implementing single-tone, multi-tone and broadband signals is verified for an input signal with a frequency ranging from 1 to 20 GHz. The mean absolute error of the frequency measurement is 34.22 MHz.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".