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.

[1]  N. A. Talcott,et al.  A review of bistatic k-space imaging for electromagnetic prediction codes for scattering and antennas , 1997 .

[2]  Hao Ling,et al.  ISAR Image Formation Using Bistatic Data Computed from the Shooting and Bouncing Ray Technique , 1993 .

[3]  Thomas Kailath,et al.  On spatial smoothing for direction-of-arrival estimation of coherent signals , 1985, IEEE Trans. Acoust. Speech Signal Process..

[4]  Chung-ching Chen,et al.  Target-Motion-Induced Radar Imaging , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[6]  Hao Ling,et al.  A model‐based angular extrapolation technique for iterative method‐of‐moments solvers , 1999 .

[7]  E. K. Miller,et al.  Using model-based parameter estimation to increase the efficiency of computing electromagnetic transfer functions , 1989 .

[8]  R. Compton,et al.  Angle and polarization estimation using ESPRIT with a polarization sensitive array , 1991 .

[9]  Hao Ling,et al.  Multi-aspect range profile extrapolation for the shooting and bouncing ray technique , 1996 .

[10]  E. K. Miller,et al.  Model-based parameter estimation in electromagnetics. I. Background and theoretical development , 1998 .

[11]  Hao Ling,et al.  A frequency extrapolation algorithm for FISC , 1997 .

[12]  R. T. Compton,et al.  Two-dimensional angle and polarization estimation using the ESPRIT algorithm , 1992 .

[13]  M. D. Deshpande,et al.  Fast RCS computation over a frequency band using method of moments in conjunction with asymptotic waveform evaluation technique , 1998 .

[14]  Dale A. Ausherman,et al.  Developments in Radar Imaging , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[15]  R. Coifman,et al.  The fast multipole method for the wave equation: a pedestrian prescription , 1993, IEEE Antennas and Propagation Magazine.

[16]  E. K. Miller,et al.  Accurate computation of wide-band response of electromagnetic systems utilizing narrow-band information , 1991 .

[17]  Thomas Kailath,et al.  ESPRIT-A subspace rotation approach to estimation of parameters of cisoids in noise , 1986, IEEE Trans. Acoust. Speech Signal Process..

[18]  Hao Ling,et al.  Radar signature prediction using moment method codes via frequency extrapolation technique , 1999 .

[19]  Raj Mittra,et al.  Combining an extrapolation technique with the method of moments for solving large scattering problems involving bodies of revolution , 1996 .

[20]  Jiming Song,et al.  Multilevel fast multipole algorithm for electromagnetic scattering by large complex objects , 1997 .