Radar Emitter Signal Feature Extraction Based on Time-Frequency Atom Decomposition

Jun Gang Li; Zhu Yu Chen; Ji Yang

doi:10.4028/www.scientific.net/AMR.694-697.1317

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697Radar Emitter Signal Feature Extraction Based on...

Radar Emitter Signal Feature Extraction Based on Time-Frequency Atom Decomposition

Abstract:

In this paper, a novel approach based on time-frequency atom decomposition is presented to recognize the radar emitter signals. To decompose the signals into a linear expansion of time-frequency atoms, a fast matching pursuit (MP) algorithm, which is optimized by composite differential evolution (CoDE) algorithm, is introduced. The feature vectors of radar emitter signals are extracted based on the atoms generated in the process of decomposition. The Directed Acyclic Graph SVM (DAGSVM) is selected as the classifier to classify the feature vectors of different radar emitter signals.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

1317-1320

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.1317

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Online since:

May 2013

Authors:

Jun Gang Li, Zhu Yu Chen, Ji Yang

Keywords:

Classifier, Feature Extraction, Radar Emitter Signal Recognition

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References

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