DocumentCode :
78679
Title :
Sharpness-Based Autofocusing for Stripmap SAR Using an Adaptive-Order Polynomial Model
Author :
Yang Gao ; Weidong Yu ; Yabo Liu ; Wang, Robert ; Chenpeng Shi
Author_Institution :
Dept. of Space Microwave Remote Sensing Syst., Inst. of Electron., Beijing, China
Volume :
11
Issue :
6
fYear :
2014
fDate :
Jun-14
Firstpage :
1086
Lastpage :
1090
Abstract :
A novel autofocusing technique is developed for image from stripmap-mode synthetic aperture radar (SAR) data. The approach is based on maximizing the image sharpness function that induces the solution to maximum-posterior estimation. In this letter, closed-form expressions are derived for the gradients of the sharpness function with respect to the coefficients of the polynomial expansion, which makes the use of conjugate gradient algorithm available. Additionally, we also design a modified adaptive-order searching strategy, and it helps to remarkably reduce the computational load while maintaining the accuracy. Real airborne SAR data experiments and comparisons demonstrate the validity and effectiveness of the proposed algorithm.
Keywords :
conjugate gradient methods; maximum likelihood estimation; optical focusing; polynomials; radar imaging; search problems; synthetic aperture radar; SAR; adaptive-order polynomial model; airborne SAR data experiment; closed-form expression; conjugate gradient algorithm; image sharpness-based autofocusing technique; maximum-posterior estimation; modified adaptive-order searching strategy; polynomial expansion coefficient; sharpness function gradient; stripmap-mode synthetic aperture radar image data; Accuracy; Adaptation models; Azimuth; Estimation; Optimization; Polynomials; Synthetic aperture radar; Autofocus; conjugate gradient method (CGM); sharpness; synthetic aperture radar (SAR);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2013.2286410
Filename :
6654245
Link To Document :
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