Title :
Generalized ISAR - part I: an optimal method for imaging large naval vessels
Author :
Given, James A. ; Schmidt, William R.
Author_Institution :
Naval Res. Lab., Washington, DC, USA
Abstract :
We describe a generalized inverse synthetic aperture radar (ISAR) process that performs well under a wide variety of conditions common to the naval ISAR tests of large vessels. In particular, the generalized ISAR process performs well in the presence of moderate intensity ship roll. The process maps localized scatterers onto peaks on the ISAR plot. However, in a generalized ISAR plot, each of the two coordinates of a peak is a fixed linear combination of the three ship coordinates of the scatterer causing the peak. Combining this process with interferometry will then provide high-accuracy three-dimensional location of the important scatterers on a ship. We show that ISAR can be performed in the presence of simultaneous roll and aspect change, provided the two Doppler rates are not too close in magnitude. We derive the equations needed for generalized ISAR, both roll driven and aspect driven, and test them against simulations performed in a variety of conditions, including large roll amplitudes.
Keywords :
electromagnetic wave scattering; military radar; radar cross-sections; radar imaging; ships; synthetic aperture radar; Doppler rate; fixed linear combination; generalized ISAR; high-accuracy three-dimensional location; inverse synthetic aperture radar; large naval vessel imaging; localized scatterer; moderate intensity ship roll; optimal method; radar cross section; radar signal processing; Geometry; Interferometry; Inverse synthetic aperture radar; Marine vehicles; Performance evaluation; Radar cross section; Radar scattering; Radar signal processing; Radio frequency; Testing; Inverse synthetic aperture radar (ISAR); radar cross section; radar signal analysis; radar signal processing; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Pattern Recognition, Automated; Radar; Ships;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2005.857283