The applicability of Compressive Sensing (CS) to ISAR has been widely discussed in the last few years. In particular, CS based ISAR image reconstruction algorithms have been developed and their effectiveness proven when dealing with incomplete ISAR data. Resolution enhancement has also been identified as a case for which CS can be effectively applied to ISAR imagery. In this case, the acquired signal can be interpreted as an incomplete data in the frequency/slow-time domain and CS used to reconstruct the super-resolved ISAR image. In this paper, an exhaustive performance analysis is carried out also as a comparison among CS and conventional super resolution techniques. Several concepts and methods are introduced in order to define effective performance analysis that is not simply based on a visual inspection.
Bistatic Inverse Synthetic Aperture Radar has recently gained interest as bistatic and multistatic radar systems are becoming increasingly popular. A theoretical foundation has been laid that introduces the concept of Bistatically Equivalent Monostatic (BEM) configuration, which allows approximating a bistatic geometry with a monostatic one. This greatly simplifies not only the geometrical understanding but also allows using monostatic ISAR processors to form bistatic ISAR images. In this paper further considerations are discussed, such as the analytical calculation of the effective rotation vector and the bistatic ISAR image plane when considering a BEM configuration. Simulated and real data analysis is also provided that prove the theoretical results
In recent years, bistatic and multistatic radar imaging systems have become popular for several applications and have gained interest within the radar scientific community. However, further issues have to be taken into account when dealing with bistatic configurations, such as synchronization and bistatic distortions. In this paper, further analysis and considerations about Bistatic ISAR (B-ISAR) theory and quadratic distortions in terms of range/Doppler migration due to the bistatic geometry are discussed. Analytical constraints for range and Doppler migration are defined by exploiting the concept of Bistatically Equivalent Monostatic (BEM) [1] and validated by means of simulated data. A super-resolution based method for bistatic distortion mitigation is then proposed and validated. Linear prediction based Bandwidth Extrapolation, Super-SVA and Compressed Sensing are tested, evaluated and compared when used for mitigating bistatic distortions
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