SAR image construction from gapped phase-history data

We propose a method for estimating the amplitude spectrum of a 2D-signal from frequency domain (or phase history) data that contain gaps. This is a key problem in synthetic aperture radar (SAR) imaging with angular diversity. Our method is an extension of the well-known amplitude and phase estimation (APES) algorithm to the incomplete data case, and is called gapped-data APES (GAPES). It has recently been shown that APES minimizes a certain least-squares (LS) criterion, and our extension of APES is based on minimizing this criterion with respect to the missing data as well. We provide an example of the algorithm applied to SAR imaging from phase history data with angular diversity; and we also show the advantages of 2D data processing over 1D (row or column-wise) data processing that are enabled by our new algorithm