A Zero-IF Auto-Calibration System For Phased Array Antennas
Bibliographic record
Abstract
A simple, compact, and low-cost implementation of an auto-calibration system for evaluating a Ka-band phased array active element is presented. The proposed technique estimates the amplitude/phase unbalance of each antenna element induced by feed circuit and characterizes phase shifter and variable gain amplifier (VGA) attached to each individual antenna element in an array configuration. This intelligent calibration system employs phased locked loop (PLL) oscillators to generate an RF test signal and a LO calibration signal. The former is used for down-converting the signal output from the antenna element under test for phase and amplitude measurement. The latter is used to compensate the quadrature mixer error in low-IF topology. The antenna signal amplitude and phase are extracted from the I/Q signals. This approach can compensate for most of the associated errors caused by nonlinearity of the quadrature modules and amplifiers using internal time-varying phase. A back-to-back measurement shows the proposed scheme can offer an accuracy of ±2 degrees in phase and ±0.3 dB in amplitude over a 30-dB dynamic range.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".