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SAR deception jamming identification via differential feature enhancement

Authors: Bo Zhao; Lei Huang; Chunlong He; Chongtao Guo; Jihong Zhang; Jinwei Wang;

SAR deception jamming identification via differential feature enhancement

Abstract

This paper proposes a new scheme for SAR deception jamming identification using single channel data. The time-frequency distributions of the real echoes and the deception jamming are modeled according to their formatting mechanisms. By filtering in the Doppler frequency domain, the differential features of the real and the false targets are retained. Then the distances between histograms are calculated to enhance the feature for false target identification. Targets in different size are set in the simulating experiment to verify the effectiveness of the proposed method.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Found an issue? Give us feedback
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!
8
Top 10%
Top 10%
Average
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