Millimetre wave isar imaging technique based on sparse aperture data collection

The millimetre wave (MW) applications has become very popular in recent years due to the high-resolution requirement in inverse synthetic aperture radar (ISAR) imaging. The most important problem encountered in MW imaging method is the high data collection requirement. Compressed sensing (CS) is often used in MW applications because it allows processing of signals with a sampling number below the Nyquist rate. However, since existing techniques used in CS take random samples from all spatial-frequency ISAR data, too many data collection probes are needed. In this study, CS based ISAR image is reconstructed by taking random samples from only synthetic aperture data instead of all spatial-frequency ISAR data. So, this type of data collection mechanism offers a much more practical application area for CS based ISAR imaging. The proposed method was verified by simulation results and the quality of the images were evaluated calculating ISLR.