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

Abstract

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 one‐dimensional (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.