Compressive sensing for in depth focusing in 3D automotive imaging radar

Today, there is a growing attention to automotive sensors monitoring systems, in order to make them an effective and valuable aid in situations of danger, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in poor weather conditions (such as fog, rain) and in presence of smoke. This limitation can be overcome by using radar sensors. In particular, imaging radar are gaining interest in the framework of Driver Assistance Systems (DAS). In this paper we propose a novel radar signal processing technique, based on Compressive Sensing (CS) theory, to perform the imaging of two or more targets on the same line of sight, greatly improving the performances of a radar DAS. After a brief description of the proposed methodology, case studies are presented in order to evaluate the performances of the technique.