Regularized least squares phase sampling interferometry

Abstract

In phase sampling interferometry, existing temporal analysis methods are sensitive to border effects and cannot deal with missing data. In this work we propose a quadrature filter that allows a reliable dynamic phase measurement for every sample, even in the cases involving few samples or missing data. The method is based on the use of a regularized least squares cost function that enforces the quadrature character of the filter. A comparison with existing techniques shows the effectiveness of the proposed method.