Research And Implement On Methods Of SAR Image Sidelobe Suppression And Target Recognition

Synthetic Aperture Radar(SAR)has been widely used in military and civilian fields in recent years.Target recognition is the key technology in image interpretation of synthetic aperture radar.The quality of synthetic aperture radar images directly affects the effect of target recognition.Therefore,how to improve the image quality and enhance the target recognition effect is a research hotspot in the field of synthetic aperture radar image processing.In this paper,sidelobe suppression and target recognition methods in synthetic aperture radar image processing are studied and implemented.The main contents of this paper are listed as follows:1.Synthetic aperture radar image sidelobe suppression methods are studied,and a synthetic aperture radar image sidelobe suppression method based on wavelet transform and spatial variant apodization is proposed.2D wavelet decomposition is carried out for the real and imaginary parts of the complex image after imaging respectively,and the sub-channels obtained after the decomposition are then implemented by the spatial variant apodization sidelobe suppression algorithm.Reconstruct the real part data and imaginary part data by using the sub-channel data after the sidelobe suppression.Then,the real part data and the imaginary part data are subjected to spatial variant apodization sidelobe suppression respectively,and finally,the complex image after wavelet transform spatial variant apodization sidelobe suppression is obtained.2.Synthetic aperture radar image target recognition methods are studied and a synthetic aperture radar image target recognition method based on multi-linear principal component analysis and tensor analysis is proposed.A four-order tensor training sample is constructed.Multi-linear principal component analysis is used to get the multi-linear projection matrix,and the core tensor is obtained from the multi-linear projection matrix.Finally,linear discriminant analysis is applied to train the core tensor and classify the test samples.3.The proposed synthetic aperture radar image sidelobe suppression method based on wavelet transform and spatial variant apodization and synthetic aperture radar image targetrecognition method based on multi-linear principal component analysis and tensor analysis are implemented in SAR target recognition system.The data import module,image preprocessing module,and target recognition module are designed and implemented in the system,and the feasibility and validity of the methods are proved by the implementation of the system.