Automatic Classification of Radar Emitter Signals Based on Cascade Feature Extractions
Laizhao Hu · Journal of Southwest Jiaotong University · 2007
A scheme of automatic classification of radar emitter signals was presented,which is based on cascade feature extractions.First,an improved instantaneous autocorrelation algorithm is performed to extract instantaneous frequencies of typical radar emitter signals.Then,the extracted instantaneous frequencies are normalized twice to obtain the classification characteristic vector.Finally,the hierarchical decision approach is used to classify radar signals automatically.The results of simulation show that the classification characteristics vector has good separation property between clusters,and the proposed approach achieves a correct rate of above 90%,even when the signal-to-noise ratio is as low as 6 dB.