Framework design of SAR target recognition via combination of 3-D scattering center model and deep learning
It is of important meaning to consistently improve Synthetic Aperture Radar(SAR)target recog-nition capability for all-day,all-weather battlefield reconnaissance.In recent years,deep leaning models have widely used and verified in the field of SAR target recognition.However,as the samples of SAR images are often very limited,the adaptivity of the models is restricted to some extent.A framework for SAR target recognition is proposed via the combination of 3-D scattering center model and deep learning,which comprehensively employs the advantages of 3-D scattering center model for SAR data generation and physical properties descriptions thus improving the classification reliability and adaptivity of deep learning models.
SARtarget recognition3-D scattering center modeldeep learning
NETL
NSTL
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