Simulation of Fresnel based beam focusing and steering for a crossed electrode array
Bibliographic record
Abstract
Fresnel based beamforming has been investigated for use with a high frequency crossed electrode array. A Fresnel zone plate uses a pattern of in phase and phase reversed pulses across the aperture chosen based on the distance from the element to the focus. The pattern of positive and negative pulses can be achieved using an array material whose response depends on a DC bias (e.g. electrostrictive ceramics, CMUTs) and applying either a positive or negative voltage. Fresnel based focusing introduces a challenge in pulsed ultrasound applications. The delays are quantized to 0 or ?/2, therefore, the pulses do not properly overlap when the difference in element-focus distance exceeds a wavelength. Because of this, the bandwidth is reduced below an acceptable standard for pulsed imaging. We have developed a novel design that pulses separate sub-apertures of the array while compensating for the delay error in each section. In exchange, the number of transmit events increases. A Fresnel approach is advantageous for a crossed electrode array using the following scheme. The Fresnel aperture focuses in azimuth on transmit while the elevational elements are beamformed traditionally. Between transmit and receive events the signals switch sides. The biases are applied in elevation and dynamic receive beamforming can be completed in azimuth and a two-way focus is achieved. A 40MHz crossed electrode array with 64 elevational and 64 azimuthal elements was simulated using Field II software. The results were compared with a 64x64 element traditionally beamformed 2D array. The two-way radiation patterns from the crossed electrode array using the Fresnel approach show -6dB beamwidths comparable to the 4096 element array but requires only 128 array connections. The resolution was 102, 126 and 151 µm when steered to 0, 15 and 25 degrees respectively. The side lobe levels raised by 15dB using the Fresnel approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".