Novel ISAR autofocusing method based on Bayesian inference

Abstract

To achieve well-focused ISAR imaging with low signal-to-noise ratio (SNR), this study constructs a statistical model and derives an effective method for image autofocusing based on Bayesian inference. Particularly, hierarchical sparse-promoting priors are imposed on the weights, which are conjugate to the likelihood. The method has closed-form solution which facilitates computation. Experimental results have demonstrated the effectiveness of the method in low SNR and short aperture scenarios.

Keywords

• Bayes methods
• radar imaging
• synthetic aperture radar
• inference mechanisms
• statistical analysis
• radar computing
• Bayesian inference
• ISAR imaging
• statistical model
• image autofocusing
• closed-form solution
• signal-to-noise ratio
• SNR
• ISAR autofocusing method
• hierarchical sparse-promoting priors