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SAR image autofocus by sharpness optimization: A theoretical study
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DOI：10.1109/TIP.2007.903252.png)
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摘要
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Synthetic aperture radar (SAR) autofocus techniques that optimize sharpness metrics can produce excellent restorations in comparison with conventional autofocus approaches. To help formalize the understanding of metric-based SAR autofocus methods, and to gain more insight into their performance, we present a theoretical analysis of these techniques using simple image models. Specifically, we consider the intensity-squared metric, and a dominant point-targets image model, and derive expressions for the resulting objective function. We examine the conditions under which the perfectly focused image models correspond to stationary points of the objective function. A key contribution is that we demonstrate formally, for the specific case of intensity-squared minimization autofocus, the mechanism by which metric-based methods utilize the multichannel defocusing model of SAR autofocus to enforce the stationary point property for multiple image columns. Furthermore, our analysis shows that the objective function has a special separble property through which it can be well approximated locally by a sum of I-D functions of each phase error component. This allows fast performance through solving a sequence of I-D optimization problems for each phase component simultaneously. Simulation results using the proposed models and actual SAR imagery confirm that the analysis extends well to realistic situations.
Keyword:
autofocus
iterative methods
sharpness optimization
sparsity condition
synthetic aperture radar (SAR)
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期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
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A TOMOGRAPHIC FORMULATION OF SPOTLIGHT-MODE SYNTHETIC APERTURE RADAR.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
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