The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band
Abstract
The market for driver assistance systems based on millimeter-wave radar sensor technology is gaining momentum. In the near future, the full range of newly introduced car models will be equipped with radar based systems which leads to high volume production with low cost potential. This paper provides background and an overview of the state of the art of millimeter-wave technology for automotive radar applications, including two actual silicon based fully integrated radar chips. Several advanced packaging concepts and antenna systems are presented and discussed in detail. Finally measurement results of the fully integrated radar front ends are shown.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions
Rasshofer, R. H., & Gresser, K. (2005) · Advances in Radio Science · doi:10.5194/ars-3-205-2005 · Cited by 252
Cited by
Automotive Radar — From First Efforts to Future Systems
Waldschmidt, C., Hasch, J., & Menzel, W. (2021) · IEEE Journal of Microwaves · doi:10.1109/jmw.2020.3033616 · Cited by 580
Self-citationXu, J., Pan, S., Sun, P. Z. H., Hyeong Park, S., & Guo, K. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3225782 · Cited by 120
Metadata
- Authors
- Hasch, J., Topak, E., Schnabel, R., Zwick, T., Weigel, R., & Waldschmidt, C.
- Venue
- IEEE Transactions on Microwave Theory and Techniques
- Published
- 2012-03
- Volume
- 60
- Issue
- 3
- Pages
- 845-860
- ISSN
- 0018-9480 (ISSN-L)
- 1557-9670
- OpenAlex
- W2050982928
- Cited by
- 1,372
- References
- 1
- FWCI
- 63.74
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band. https://app.cochat.ai/papers/10.1109/tmtt.2011.2178427
- The paper
- Hasch, J., Topak, E., Schnabel, R., Zwick, T., Weigel, R., & Waldschmidt, C. (2012). Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band. IEEE Transactions on Microwave Theory and Techniques. https://doi.org/10.1109/tmtt.2011.2178427
Data sources
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.
