The present invention discloses a ground target detection and localization method for SAR images based on electromagnetic strong scattering points. The method comprises: preprocessing the obtained polarization SAR images; using threshold segmentation to locate a potential region of a target, and obtaining a region of interest (ROI) of the target through morphological processing and clustering; extracting strong scattering point features; establishing a three-dimensional model pf the target according to a target type library; establishing a strong scattering point model of the target under different azimuth angles; performing echo data simulation according to the established strong scattering point model to obtain a one-dimensional distance image of the target under different azimuth angles; extracting strong scattering point features by using the one-dimensional distance image, and selecting and normalizing the features; and training a SVM classifier for the normalized strong scattering point features, and performing feature matching between the normalized strong scattering point features and the strong scattering point features extracted from the POI to obtain an identification result. The method provided by the present invention can be used for ground target detection and classification identification, so that the target position can be effectively located and the subsequenttarget tracking can be performed.