Regularized least squares phase sampling interferometry

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.