Radar emitter signal recognition based on multi-scale wavelet entropy and feature weighting

In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. W...

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Bibliographic Details
Published inJournal of Central South University Vol. 21; no. 11; pp. 4254 - 4260
Main Authors Li, Yi-bing, Ge, Juan, Lin, Yun, Ye, Fang
Format Journal Article
LanguageEnglish
Published Heidelberg Central South University 01.11.2014
Subjects
Engineering
Metallic Materials
emitter recognition
stability weight factor
feature weighting
multi-scale wavelet entropy
uneven weight factor
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Summary:In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio (SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than -4 dB, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.
ISSN:2095-2899
2227-5223
DOI:10.1007/s11771-014-2422-5