Wavelength-Resolution SAR Change Detection Using Bayes’ Theorem

Abstract

-This article presents Bayes' theorem for wavelength-resolution synthetic aperture radar (SAR) change detection method development. Different change detection methods can be derived using Bayes' theorem in combination with the target model, clutter-plus-noise model, iterative implementation, and noniterative implementation. As an example of the Bayes' theorem use for wavelength-resolution SAR change detection method development, we propose a simple change detection method with a clutter-plus-noise model and noniterative implementation. In spite of simplicity, the proposed method provides a very competitive performance in terms of probability of detection and false alarm rate. The best result was a probability of detection of 98.7% versus a false alarm rate of one per square kilometer.

Keywords

• Bayes’ theorem
• CARABAS
• change detection
• synthetic aperture radar (SAR)
• wavelength resolution