Title :
Separation of scattering phenomena in super-resolution ISAR imaging using constrained music
Author :
Jon Mitchell;Saibun Tjuatja
Author_Institution :
Wave Scattering Research Center, Department of Electrical Engineering, The University of Texas at Arlington, UTA Box 19016, Arlington, TX 76019
fDate :
7/1/2015 12:00:00 AM
Abstract :
In ISAR Multiple Signal Classification (MUSIC) imaging, the target is generally modeled as a collection of point scatterers. This simplistic model is robust but does not accurately image other scattering phenomena such as physical optics scattering from targets that are large with respect to wavelength. Utilization of the point scattering model for MUSIC imaging of physical optics scattering results in the distribution of target energy across several image pixels. This abstract introduces a method for separating scattering returns from objects with distinct size and shape or with different scattering mechanisms. A new scattering model is proposed to estimate physical optics scattering from spherical scatterers. Using constrained MUSIC techniques, returns from scatterers with a specific size and shape can be eliminated from the super-resolution ISAR image.
Keywords :
"Multiple signal classification","Scattering","Clutter","Imaging","Physical optics","Mathematical model","Reflection"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326086