Harmonic Radar Transceiver Design: Miniature Tags for Insect Tracking
Bibliographic record
Abstract
The design and operation along with verifying measurements of a harmonic radar transceiver, or tag, developed for insect tracking are presented. A short length of wire formed the antenna while a beam lead Schottky diode across a resonant loop formed the frequency doubler circuit yielding a total tag mass of less than 3 mg. Simulators using the method-of-moments for the antenna, finite-integral time-domain for the loop, and harmonic balance for the nonlinear diode element were used to predict and optimize the transceiver performance. This performance is compared to the ideal case and to measurements performed using a pulsed magnetron source within an anechoic chamber. A method for analysis of the tag is presented and used to optimize the design by creating the largest possible return signal at the second harmonic frequency for a particular incident power density. These methods were verified through measurement of tags both in isolation and mounted on insects. For excitation at 9.41 GHz the optimum tag in isolation had an antenna length of 12 mm with a loop diameter of 1 mm which yielded a harmonic cross-section of 40 mm/sup 2/. For tags mounted on Colorado potato beetles, optimum performance was achieved with an 8 mm dipole fed 2 mm from the beetle attached end. A theory is developed that describes harmonic radar in a fashion similar to the conventional radar range equation but with harmonic cross-section replacing the conventional radar cross-section. This method provides a straightforward description of harmonic radar system performance as well as provides a means to describe harmonic radar tag performance.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".