DocumentCode :
1796975
Title :
Uniform rotational motion compensation for inverse synthetic aperture radar targets from image domain
Author :
Zhiwei Xu ; Lei Zhang ; Mengdao Xing ; Gang Xu
Author_Institution :
Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´an, China
fYear :
2014
fDate :
9-13 July 2014
Firstpage :
166
Lastpage :
170
Abstract :
Since high-resolution inverse synthetic radar (ISAR) images are significant in the analysis of moving targets, this paper, for the first time, proposes a novel method to compensate the uniform rotational motion by estimating the effective rotational velocity (ERV) in image domain. Specifically, we extract high-energy scatterers of sequent ISAR images by scale invariant feature transform (SIFT) in order to link them with the related ERV in the imaging panel. Then we adopt registering approach based on minimum Euclidian distance and Gaussian probabilistic density function to select scatterers with the mostly similar rotational aspect. After that, we estimate the ERV in a searching manner, and then employ it in the cancellation of quadratic-order phase items in the cross-range cells of the image. This method is validated quick and efficient by both simulated and real signal experiments.
Keywords :
Gaussian processes; image registration; image resolution; motion compensation; probability; radar imaging; radar resolution; synthetic aperture radar; ERV; Gaussian probabilistic density function; ISAR images; SIFT; cross-range cells; effective rotational velocity; high-energy scatterer extraction; high-resolution inverse synthetic radar; image domain; image registering approach; imaging panel; inverse synthetic aperture radar targets; minimum Euclidian distance; moving target analysis; quadratic-order phase item cancellation; scale invariant feature transform; uniform rotational motion compensation; Entropy; Estimation; Feature extraction; Image resolution; Radar imaging; Signal resolution; Inverse synthetic aperture radar (ISAR); effective rotational velocity (ERV) estimation; image domain; scale invariant feature transform (SIFT); scatter registration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-5401-8
Type :
conf
DOI :
10.1109/ChinaSIP.2014.6889224
Filename :
6889224
Link To Document :
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