Real-Time 2-D FIR Trapezoidal Digital Filters for 2.4 GHz Aperture Receiver Applications
Bibliographic record
Abstract
This paper presents the implementation of a two-dimensional (2-D) finite-impulse-response (FIR) trapezoidal filter based beamforming array receiver. A 2.4 GHz 16-element receive-mode IQ array is designed and used for physically measuring the beam patterns corresponding to 2-D FIR trapezoidal filters. The 16-element beamformer is implemented using the reconfigurable open architecture computing hardware version-2 (ROACH-2) field programmable gate array (FPGA) platform to perform analog to digital conversion and digital signal processing. The 2-D FIR trapezoidal filter is designed as a 16-spatial input 32-tap filter and is implemented targeting the ROACH-2’s Xilinx Virtex 6 (sx475t) FPGA chip as a filter-and-sum architecture. The receiver array is precisely rotated (keeping the transmitter fixed) to digitally measure the received energy by integrating the instantaneous power of the output of the 2-D FIR trapezoidal filter for each angle of reception. The main lobe of the measured beam pattern is well aligned with the simulated beam pattern, and the highest measured side-lobe level is −17.8 dB.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".