An overview of latest advancements in displaced phase centre antenna (DPCA) techniques
Bibliographic record
Abstract
In certain applications, such as radars, remote sensing, and precise global positioning systems, the phase reference of the radio frequency (RF) system is of great importance as it affects the system accuracy, such that even small uncertainty could lead to big errors. In wireless communications, this phase reference is dominated by the antennas, the last components of the RF front-end parts, which radiate the Electromagnetic waves. Thus, knowledge of the antenna phase reference, well known as the phase centre, is vital in aforementioned applications. The phase centre location of an antenna is the effective source of radiation providing a uniform phase pattern at the far-field zone over a finite angular range in space, which is normally around the main beam. Therefore, any phase centre displacement will move the phase reference of the communication system. Particularly, in moving target indicator radars, where the antenna part is mounted on a moving platform, the forward motion of the moving platform changes the effective phase centre location of the operating antenna. This could result in errors as significant as missing low velocity objects. One of the techniques to overcome this problem is the displaced phase centre antenna (DPCA) processing technique [M. I. Skolnik, Radar Handbook, McGraw-Hill, 1990]. Traditionally, DPCA technique exploits two or more identical aperture antennas, which provide separate phase centre locations with identical secondary radiation patterns. This will, however, increase the hardware and complexity of the antenna systems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".