A frequency-aspect extrapolation algorithm for ISAR image simulation based on two-dimensional ESPRIT

A frequency-aspect extrapolation algorithm is proposed to accelerate ISAR image simulation using fast multipole solvers. A two-dimensional (2D) multiple-arrival model based on high-frequency physics is proposed to parameterize the induced currents on the target. A 2D estimation of parameters via rotation invariance technique (ESPRIT) algorithm is developed to estimate the model parameters from a limited number of computed data samples in frequency and aspect. The model is then extrapolated to other frequencies and aspects to arrive at broadband, wide-angle radar cross section (RCS) data for inverse synthetic aperture radar (ISAR) image construction. This algorithm is tested using a canonical cylinder-plate structure to evaluate its performance. The ISAR image of the benchmark VFY-218 airplane at UHF band is then predicted using the fast multipole solver FISC and the 2D extrapolation algorithm. The resulting image compares favorably with that obtained from chamber measurement data