A COMPARATIVE STUDY ON ISAR IMAGING ALGORITHMS FOR RADAR TARGET INDENTIFICATION

Title
A COMPARATIVE STUDY ON ISAR IMAGING ALGORITHMS FOR RADAR TARGET INDENTIFICATION
Author(s)
김경태박종일
Keywords
PARTICLE SWARM OPTIMIZATION; HOUGH TRANSFORM; MUSIC ALGORITHM; RECOGNITION; DISCRIMINATION; IDENTIFICATION; PREDICTION; SCATTERING; AUTOFOCUS; ENTROPY
Issue Date
201009
Publisher
E M W PUBLISHING
Citation
PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER, v.108, pp.155 - 175
Abstract
Inverse synthetic aperture radar (ISAR) images represent the two-dimensional (2-D) spatial distribution of the radar cross-section (RCS) of an object and, thus, they can be applied to the problem of target identification. The traditional approach to ISAR imaging is the range-Doppler algorithm based on the 2-D Fourier transform. However, the 2-D Fourier transform often results in poor resolution ISAR images, especially when the measured frequency bandwidth and angular region are limited. Instead of the Fourier transform, high resolution spectral estimation techniques can be adopted to improve the resolution of ISAR images. These are the autoregressive (AR) model, multiple signal classification (MUSIC), and matrix enhancement and matrix pencil MUSIC (MEMP-MUSIC). In this study, the ISAR images from these high-resolution spectral estimators, as well as the FFT approach, are identified using a recently developed identification algorithm based on the polar mapping of ISAR images. In addition, each ISAR imaging algorithm is analyzed and compared in the framework of radar target identification. The results show that the dynamic range as well as the resolution of the ISAR images plays an important role in the identification performance. Moreover, the optimum size of the subarray (i.e., covariance matrix) for MUSIC and MEMP-MUSIC in terms of target identification is expeimentally derived.
URI
http://hdl.handle.net/YU.REPOSITORY/23716http://dx.doi.org/10.2528/PIER10071901
ISSN
1559-8985
Appears in Collections:
공과대학 > 전자공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE