57-64 GHz Imaging/Detection Sensor–Part I: System Setup and Experimental Evaluations
Bibliographic record
Abstract
A novel experimental evaluation of millimeterwave imaging / detection system based on time domain reflectometry (TDR) is presented. The proposed 60 GHz-band system is characterized by high precision, lightweight, low profile, and utilization of low cost scanning probes. As a scanning sensor, multi sin-corrugation antipodal tapered slot antenna (MC-AFTSA-SC) with and without a grooved spherical probe is introduced. Although, the precise mechanical setup is especially designed and optimized to hold the proposed scanning probe antenna, it can handle a wide range of probes. The proposed antenna sensor is experimentally evaluated by integrating it in the proposed imaging/detection system. As a bench-marking process, multiple images for different targets are reconstructed using both the proposed probe and conventional standard gain horn (SGH) antenna. The images are generated using 2D linear scanning platform with a cross range resolution δx = δy = 3mm achieving a 100 × 100 pixels image. The obtained images indicate a superior performance of the proposed scanning probe over the bigger sized SGH. This paper is split into two parts because of its length: this paper (part I) describes the system setup and experimental evaluation of the probes, while part II will discuss experiments for detecting concealed weapons and threatening materials.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".