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Signal interception: a unifying theoretical framework for feature detection
Abstract
The unifying framework of the spectral-correlation theory of cyclostationary signals is used to present a broad treatment of weak, random signal detection for interception purposes. The relationships among a variety of previously proposed ad hoc detectors, optimum detectors, and newly proposed detectors are established. The spectral-correlation-plane approach to the interception problem is put forth as especially promising for detection, classification, and estimation in particularly difficult environments involving unknown and changing noise levels and interference activity. A fundamental drawback of the popular radiometric methods in such environments is explained.>
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Citations
Cited by
SNR Walls for Signal Detection
Tandra, R., & Sahai, A. (2008) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2007.914879 · Cited by 1,544
A new approach to signal classification using spectral correlation and neural networks
Fehske, A., Gaeddert, J., & Reed, J. H. (2005) · First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005. · doi:10.1109/dyspan.2005.1542629 · Cited by 447
Metadata
- Authors
- Gardner, W. A.
- Venue
- IEEE Transactions on Communications
- Published
- 1988
- Volume
- 36
- Issue
- 8
- Pages
- 897-906
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W2151946103
- Cited by
- 609
- References
- 0
- FWCI
- 5.41
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gardner, W. A. (1988). Signal interception: a unifying theoretical framework for feature detection. IEEE Transactions on Communications. https://doi.org/10.1109/26.3769
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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.
