Active and Passive Multi-Sensor Radar Imaging Techniques Exploiting Spatial Diversity

The work here presented reports several innovative SAR and ISAR radar imaging techniques exploiting the spatial diversity offered by multi-sensor systems in order to improve the performance with respect to the conventional, single channel cases. Both the cases of dedicated transmitters and exploitation of opportunity transmitters are considered

Active and Passive Multi-Sensor Radar Imaging Techniques Exploiting Spatial Diversity

The work here presented reports several innovative SAR and ISAR radar imaging techniques exploiting the spatial diversity offered by multi-sensor systems in order to improve the performance with respect to the conventional, single channel cases. Both the cases of dedicated transmitters and exploitation of opportunity transmitters are considered

Multichannel techniques for 3D ISAR

This thesis deals with the challenge of forming 3D target reconstruction by using spatial multi-channel ISAR configurations. The standard output of an ISAR imaging system is a 2D projection of the true three-dimensional target reflectivity onto an image plane. The orientation of the image plane cannot be predicted a priori as it strongly depends on the radar-target geometry and on the target motion, which is typically unknown. This leads to a difficult interpretation of the ISAR images. In this scenario, this thesis aim to give possible solutions to such problems by proposing three 3D processing based on interferometry, beamforming techniques and MIMO InISAR systems. The CLEAN method for scattering centres extraction is extended to multichannel ISAR systems and a multistatic 3D target reconstruction that is based on a incoherent technique is suggested

Multichannel techniques for 3D ISAR

This thesis deals with the challenge of forming 3D target reconstruction by using spatial multi-channel ISAR configurations. The standard output of an ISAR imaging system is a 2D projection of the true three-dimensional target reflectivity onto an image plane. The orientation of the image plane cannot be predicted a priori as it strongly depends on the radar-target geometry and on the target motion, which is typically unknown. This leads to a difficult interpretation of the ISAR images. In this scenario, this thesis aim to give possible solutions to such problems by proposing three 3D processing based on interferometry, beamforming techniques and MIMO InISAR systems. The CLEAN method for scattering centres extraction is extended to multichannel ISAR systems and a multistatic 3D target reconstruction that is based on a incoherent technique is suggested

Compressive sensing for interferometric inverse synthetic aperture radar applications

The applicability of interferometric inverse synthetic aperture radar (InISAR) techniques to images reconstructed via compressive sensing (CS)-based algorithms is investigated. Specifically, the three-dimensional (3D) reconstruction algorithm is applied after exploiting CS for data compression and image reconstruction. The InISAR signal model is derived and formalised in a CS framework. A comparison between conventional CS reconstruction and global sparsity constrained reconstruction techniques is performed for different compression rates and different signal-to-noise ratio conditions. Performances on the 2D and 3D reconstructions are evaluated. Results obtained on real data acquired during the NATO-SET 196 trial are shown