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A multiline method of network analyzer calibration
Open accessAbstract
The author presents a method for the calibration of network analyzers. The essential feature is the use of multiple, redundant transmission line standards. The additional information provided by the redundant standards is used to minimize the effects of random errors, such as those caused by imperfect connector repeatability. The resulting method exhibits improvements in both accuracy and bandwidth over conventional methods. The basis of the statistical treatment is a linearized error analysis of the TRL (thru-reflect-line) calibration method. The analysis presented is useful in the assessment of calibration accuracy. It also yields results relevant to the choice of standards.>
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Cited by
Efficient and robust analysis of complex scattering data under noise in microwave resonators
Probst, S., Song, F. B., Bushev, P. A., Ustinov, A. V., & Weides, M. (2015) · Review of Scientific Instruments · doi:10.1063/1.4907935 · Cited by 301
Metrology State-of-the-Art and Challenges in Broadband Phase-Sensitive Terahertz Measurements
Naftaly, M., Clarke, R. G., Humphreys, D. A., & Ridler, N. M. (2017) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2644108 · Cited by 49
Metadata
- Authors
- Marks, R. B.
- Venue
- IEEE Transactions on Microwave Theory and Techniques
- Published
- 1991-07
- Volume
- 39
- Issue
- 7
- Pages
- 1205-1215
- ISSN
- 0018-9480 (ISSN-L)
- OpenAlex
- W2168854778
- Cited by
- 1,285
- References
- 0
- FWCI
- 15.21
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: A multiline method of network analyzer calibration. https://app.cochat.ai/papers/10.1109/22.85388
- The paper
- Marks, R. B. (1991). A multiline method of network analyzer calibration. IEEE Transactions on Microwave Theory and Techniques. https://doi.org/10.1109/22.85388
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.