A Survey of Phase Shifters for Microwave Phased Array Systems
Bibliographic record
Abstract
ABSTRACT Phased Array Systems (PASs) are extensively used in radar and telecommunication systems for diverse applications, including military surveillance and wireless broadband communication. Besides, they are becoming increasingly indispensable in modern applications such as multi‐function phased array radars for weather monitoring and aircraft tracking or high‐throughput satellite systems, which aim to provide fast broadband connectivity in remote areas. Despite the numerous advantages of phased array systems with RF phase shift, including high signal‐to‐noise and signal‐to‐interference ratios, as well as low complexity, they present a few limitations, including high cost and large chip areas. The cost and size of PASs are mainly dependent on the RF phase shifters, which are essential to their operation. This article describes the different types of phase shifters (mechanical, ferromagnetic/magnetic, electromechanical, and electronic). It compares their performance metrics, highlighting that electronic phase shifters are the most common type used in modern PASs. In this regard, a comparative study of different subcategories of electronic phase shifters, such as the switched‐type, reflective‐type, loaded‐transmission line, and vector‐sum phase shifters, are explored along with their advantages, drawbacks and state‐of‐art techniques used to address their limitations. Therefore, this article may serve as a reference for research milestones on RF phase shifters.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".