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This paper introduces an efficient approach to radar signal automatic classification by extracted fusion feature entropy. In this approach, wavelet packet reconstruct coefficient features are extracted from given radar signals in frequency domain based on wavelet packet decomposition. Then, these features are fused with the principal component analysis and a single characteristic feature vector which...
An effective approach to classify the radar emitter signals is presented, which is based on a cascade feature extractions and a hierarchical decision technique. Firstly, the instantaneous autocorrelation, improved by non-ambiguity phase expansion and moving average, is used to extract the primary instantaneous frequencies of radar signals. Then, a successive normalization-based feature re-extraction...
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