ISAR image reconstruction from periodically gapped data

In practical radar imagery operations, there are often cases where the radar´s operating bandwidth is interrupted, either periodically or randomly. Such interruption produces artifacts in synthetic aperture radar (SAR) and inverse SAR (ISAR) images, and thus severely degrades the reconstructed images. As a consequence, novel image processing algorithms are required to alleviate the artifacts for high quality images. Various algorithms for SAR/ISAR image reconstruction from periodically gapped data have been developed. These include extensions of the APES and the Capon methods, such as periodically-gapped Capon (PG-Capon) and PG-APES (Larsson, E.G. and Li, J., IEEE Trans. Aerospace and Electronic Systems, vol.39, no.3, p.1089-97, 2003). Based on Larsson and Li´s work, we develop 2D PG-Capon and PG-APES algorithms for ISAR image reconstruction from periodically gapped data. Image reconstruction examples are presented to demonstrate the effectiveness of the current procedures with comparison to the results by their 1D versions and by the coherent CLEAN algorithm.