Orthogonal Coded Active Illumination for Millimeter Wave, Massive-MIMO Computational Imaging With Metasurface Antennas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emerging metasurface antenna technology enables flexible and low cost massive multiple-input multiple-output (MIMO) millimeter-wave (mmW) imaging for applications such as personnel screening, weapon detection, reconnaissance, and remote sensing. This work proposes an orthogonal coded active illumination (OCAI) approach which utilizes simultaneous, mutually orthogonal coded transmit signals to illuminate the scene being imaged. It is shown that OCAI is robust to code amplitude and code phase imbalance introduced by imperfect transmitter (TX) and receiver (RX) hardware, while also mitigating common impairments of low cost direct-conversion receivers, such as RX self-jamming and DC offsets. The coding gain offered by this approach improves imager signal to noise ratio performance by up to 15 dB using codes of symbol length 32. We present validation images of resolution targets and a human-scale mannequin, obtained with a custom massive-MIMO mmW imager having 24 simultaneous TXs and 72 simultaneous RXs operating in the K-band (17.5 GHz to 26.5 GHz). The imager leverages both spatial coding via frequency diverse metasurface antennas, and temporal coding via OCAI of the scene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it