A quasi-parametric algorithm for synthetic aperture radar target feature extraction and imaging with angle diversity

We present synthetic aperture radar (SAR) target feature extraction and imaging techniques with angle divesity. We first establish a flexible data model that describes each target scatterer as a two-dimensional (2D) complex sequence with arbitrary amplitude and constant phase in range and cross-range. A new algorithm, referred to as the QUasiparametric ALgorithm for target feature Extraction (QUALE), is then presented for SAR target feature extraction via data fusion through angle diversity based on the flexible data model. QUALE first estimates the model parameters, which include, for each scatterer, a 2D arbitrary real-valued amplitude sequence, a constant phase, and scatterer locations in range and cross-reange. QUALE then averages the estimated 2D real-valued amplitude sequence over range by making the assumption that the scatterer radar cross section is approximately consant. QUALE next models the so-obtained 1D sequence with a simple sinc function by assuming that the scatterer is approximately a dihedral (a trihedral is approximated as a very short dihedral) and estimates the relevant sinc function parameters by minimizing a nonlinear least-squares fitting function. Finally, the approximate 2D SAR image is reconstructed by using the estimated features. Numerical examples are given to demonstrate the perfomance of the proposed algorithm.

[1]  D. D. Meisel.  Fourier transforms of data sampled in unequally spaced segments. , 1979 .

[2]  J. Scargle.  Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data , 1982 .

[3]  D. H. Roberts,et al.  Time Series Analysis with Clean - Part One - Derivation of a Spectrum , 1987 .

[4]  W. Press,et al.  Interpolation, realization, and reconstruction of noisy, irregularly sampled data , 1992 .

[5]  Demetri Psaltis,et al.  Correlation filters for aircraft identification from radar range profiles , 1993 .

[6]  Stuart R. DeGraaf,et al.  Sidelobe reduction via adaptive FIR filtering in SAR imagery , 1994, IEEE Trans. Image Process..

[7]  Victor J. Larson,et al.  Polarimetric subspace target detector for SAR data based on the Huynen dihedral model , 1995, Defense, Security, and Sensing.

[8]  Jian Li,et al.  Efficient mixed-spectrum estimation with applications to target feature extraction , 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

[9]  Jian Li,et al.  An adaptive filtering approach to spectral estimation and SAR imaging , 1996, IEEE Trans. Signal Process..

[10]  Sergio Barbarossa.  SAR super resolution imaging by signal subspace projection techniques , 1996 .

[11]  J.A. O'Sullivan,et al.  High resolution radar models for joint tracking and recognition , 1997, Proceedings of the 1997 IEEE National Radar Conference.

[12]  G.R. Benitz.  High-definition vector imaging for synthetic aperture radar , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[13]  Jian Li,et al.  Performance analysis of forward-backward matched-filterbank spectral estimators , 1998, IEEE Trans. Signal Process..

[14]  R. P. Wishner,et al.  Battlefield awareness via synergistic SAR and MTI exploitation , 1998 .

[15]  Jian Li,et al.  Implementation of the RELAX algorithm , 1998 .

[16]  Jian Li,et al.  SAR image formation via semiparametric spectral estimation , 1999 .

[17]  J. T. Mayhan,et al.  Ultrawide-band coherent processing , 1999 .