Multipath mitigation techniques based on time reversal concept and superresolution algorithms for inverse synthetic aperture radar imaging

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 'TRISAR 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.