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Feature Extraction Using Wavelet Transform for Radar Emitter Signals

Authors: Taowei Chen; Weidong Jin; Zhenxing Chen;

Feature Extraction Using Wavelet Transform for Radar Emitter Signals

Abstract

In this paper, an approach for intra-pulse feature extraction of radar emitter signals is proposed based on wavelet transform. On the basis of the multi-resolution characteristics of wavelet transform, two energy entropies, as a two-dimensional feature vector to reveal the difference of radar modulation signals, are respectively extracted from approximation coefficient and multi-scale detail coefficients preserved through inter-scale correlations denoise in wavelet transform domain. In order to demonstrate the effectiveness and feasibility of the proposed approach, computer simulations indicates that the entropy features of ten typical radar emitter signals extracted by wavelet transform have good performance of clustering and suppressing noise when SNR is 0dB. In addition, proposed approach can separate the same modulation signals with different parameters.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Top 10%
Average
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