Sparse subband fusion imaging based on parameter estimation of geometrical theory of diffraction model

This study focuses on sparse subband fusion imaging. A method based on high-precision parameter estimation of geometrical theory of diffraction (GTD) model is given. Considering the incoherence problem in each subband data, a coherent processing method is adopted in the paper. Based on an all-pole model, it makes use of the phase difference of pole and scattering coefficient between each sub-band to effectively estimate the incoherent components. After coherent processing, the high and low frequency subband data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation algorithm is adopted to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data with fixed-points indicate that the resolution of onedimensional (1D) range profile and 2D inverse synthetic aperture radar (ISAR) image based on this method is better than that of each sub-band. In this way, the validity of the proposed method is proved.