A Novel Method for Parametric Estimation of 2D Geometrical Theory of Diffraction Model Based on Compressed Sensing

The electromagnetic scattering mechanism of radar target in high frequency domain can be characterized exactly by Geometrical Theory of Diffraction (GTD) model. In this paper, a novel parameter estimating method for 2D GTD model is proposed based on the analysis of the radar echoes sparse characteristic. The parameters estimation is converted to the issue of sparse signal reconstruction in the framework of Compressed Sensing (CS). In the proposed method, the signal support is first determined using 2D Fourier transform imaging and then the parameters of GTD model are estimated from the support region. To further improve the estimation precision of the parameters, clustering algorithms and linear least squares algorithms also adopted. Experiment results from both synthetic and real data show that the presented method is superior to the ones in existence, especially for the estimation of the scattering center type.