Iterative Regularization Using an Acceleration Technique for Synthetic Aperture Interferometric Radiometer

Abstract

The inverse problem of synthetic aperture interferometric radiometers (SAIRs) aims at retrieving the brightness temperature map from the visibility function samples. To efficiently obtain an accurate solution, an accelerated iterative regularization technique is proposed to reconstruct the SAIR brightness temperature map. The acceleration technique modifies the conventional least square function using a negative penalty term to speed up the initial iterations. A series of decreasing coefficients must be tuned to prevent noise amplification in subsequent iterations. Several numerical experiments were performed on one-dimensional (1-D) and (2-D) SAIR systems. The experiment results indicate that the accelerated Landweber method reduces the number of iteration steps by more than 50% and effectively improves the computational speed without reducing the reconstruction accuracy compared to the conventional Landweber method.

Keywords

• Convergence
• interferometric radiometry
• inverse problem
• iterative regularization
• synthetic aperture