Skip to Main Content
Inverse synthetic aperture radar (ISAR) is a coherent high-resolution radar technique capable of providing range-Doppler images of non-cooperative targets. Conventional ISAR systems just consider a single reflection of transmitted waveforms from targets. Nevertheless, today's new applications force ISAR systems to work in much more complex scenarios such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor visual quality, making target detection particularly difficult. By applying time reversal concept to ISAR imaging, it is possible to reduce considerably (or even mitigate) ghosting artifacts, recovering the lost quality due to multipath effects. Nevertheless, before applying this innovative technique, it is essential to estimate the distance between radar and target for each transmitted ramp and for each target scatterer. To that end, a pre-processing algorithm based on detecting the prominent points of a conventional ISAR image corrupted by multipath, followed by a windowing process, is used. Both simulated and real data are used to verify the proposed method.