Hierarchical Mixed Signal Detection and Modulation Classification

Authors

Yang Qu, Wright State University
Zhiqiang Wu, Wright State University - Main CampusFollow
Ruolin Zhou, Wright State University
Yan Su, Wright State University

Document Type

Article

Publication Date

9-2-2020

Identifier/URL

40917397 (Pure)

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Abstract

Signal detection and modulation classification plays an important role in civil and military. In this paper, some challenging problems in signal detection and modulation classification have been discussed. We employed signal cyclostationary theory and Support Vector Machine (SVM) method to blindly detect and classify mixed signals, which have significant overlap in both time domain and frequency domain. Compared with other similar studies, our analysis and experiments are more practical and challenge. In addition, the simulation results demonstrates that our proposed approach shows great performance in different conditions and environment.

Repository Citation

Qu, Y., Wu, Z., Zhou, R., & Su, Y. (2020). Hierarchical Mixed Signal Detection and Modulation Classification. 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), 213-216.
https://corescholar.libraries.wright.edu/ee/196

DOI

10.1109/MWSCAS48704.2020.9184462