High Definition Vector
MIT Lincoln Laboratory
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Lexington, MA 02173-9108
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Abstract Foliage penetration (FOPEN) SAR presents some serious challenges for target detection and recognition since some target features are distorted or missing in foliage. The ability to extract a variety of target/scatterer features from the data should benefit performance. High Definition Vector Imaging (HDVI) constitutes a class of techniques that provide adaptive imagery with reduced sidelobe levels and, potentially, enhanced resolution. Vector imagery refers to the ability to image the data in terms of basic scatterer features such dihedrals and trihedrals or in terms of additional measurements such as polarization. The adaptive nature of the imaging allows the data to be represented in terms of one type of scattering/polarization feature while different, non-orthogonal features are suppressed. Besides providing imagery emphasizing different aspects of the data, vector imagery can also be used for discrimination of targets from clutter and for automatic target recognition (ATR).
Some algorithms for polarimetric HDVI are described. In some cases the polarizations are estimated on a per pixel basis. In all cases the polarizations are adaptively combined either coherently or incoherently to form a polarimetric image. Measured data from the P-3 Ultra Wide-Band (UWB) SAR are used to present some example imagery.
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