SAR/ISAR images have been largely used for monitoring small to large areas and in different applications more specifically for target recognition/identification. However, classical SAR/ISAR systems typically make use of single frequency, constant instantaneous bandwidth, single polarization radar systems, which may have some limitations in terms of spatial resolutions and may experience some difficulties in image interpretation. Multi-dimensional radar on the other hand benefits from a variation of specific parameters, e.g. different polarizations, illumination directions (azimuth or elevation), center frequencies, etc.

The objective of this session is to carry together new aspects in the field of multi-dimensional radar to form multi-perspective high-resolution 2D, 3D and tomographic radar images of targets, with intent of enhancing target classification and recognition. Possible topics cover algorithms for volumetric SAR, coherent and/or incoherent combination of multi-dimensional data, combination/fusion of spatial and temporal data, and investigation of AI to manage multi-dimensional data.