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-Synthetic Aperture Radar (SAR) images a target region reflectivity function in the multi-dimensional spatial domain of range and cross-range. SAR synthesizes a large aperture radar in order to achieve a finer azimuth resolution than the one provided by any on-board real antenna. Conventional SAR techniques assume a single reflection of transmitted waveforms from targets. Nevertheless, today's new scenes force SAR systems to work in urban environments. Consequently, multiple-bounce returns are added to directscatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor resolution. By analyzing the quadratic phase error (QPE), this paper demonstrates that Earth's curvature influences the defocusing degree of multipath returns. In addition to the QPE, other parameters such as integrated sidelobe ratio (ISLR), peak sidelobe ratio (PSLR), contrast (C) and entropy (E) provide us with the tools to identify direct-scatter echoes in images containing undesired returns coming from multipath.

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Radar imaging based on static high-resolution coherent radar is widely known as inverse synthetic aperture radar (ISAR) imaging. This 'all-weather' system is able to provide slant-range -Doppler images of non-cooperative targets whose motion is unknown. Conventional ISAR systems are designed for imaging targets with a direct line of sight of sensors. For this reason, they have a reduced performance in today's complex scenarios -such as urban environments -where secondary returned waveforms are added to directly reflected echoes coming from targets. They are known as ghost artefacts since they obscure true targets when using the standard range-Doppler algorithm (RDA). In this study, an innovative multipath mitigation technique is presented, in which 'time reversal (TR)' concept is implemented in ISAR images, leading to 'TR-ISAR algorithm'. For this purpose, a pre-processing algorithm is previously needed so as to solve the geometric problem related to multipath. Finally, superresolution algorithms provide us with the tools to mitigate the spurious component that arises during the averaging process carried out by TR-ISAR. The authors' conclusion is that imaging quality after employing superresolution approaches is clearly improved. As a proof-of-concept, real data from high-resolution radar have been used to verify the proposed method.