Cascade Feature Extraction for Radar Emitter Signals Based on Atomic Decomposition
Laizhao Hu, EW La · Journal of Southwest Jiaotong University · 2007
A cascade feature extraction for radar emitter signals based on atomic decomposition was proposed.Radar emitter signals are decomposed into a linear expansion of atoms by the method of matching pursuit(MP) based on an over-complete dictionary of Gaussian chirplet atoms,and an improved quantum genetic algorithm is applied to reduce the time-complexity of each search step of MP.In this way,optimal chirplet atoms representing features of signals are obtained.Then,the characteristic vectors of atoms are extracted to get strong-discrimination.Experimental results on 5 typical radar emitter signals show that the extracted atoms have good ability to cluster the same radar signals and separate different radar signals,which confirms the validity and feasibility of the proposed approach.