We designed a ground-based radar system with a C-band 2-D cross multiple input multiple output (MIMO) array for 3-D imaging and displacement estimation purposes. For this system, we developed a far-field pseudo-polar image format algorithm using pseudo-polar spherical coordinate. The use of a tensor compressive sensing technique allows to focus under-sampled raw data and to optimize the data acquisition time and memory usage. A novel algorithm, named as tensor-based iterative adaptive approach, is proposed for the effective and efficient reconstruction of sparse targets with a reduced level of sidelobes. Experimental results validate the designed radar system and the proposed algorithms.

3-D Ground-Based Imaging Radar Based on C-Band Cross-MIMO Array and Tensor Compressive Sensing

Nico Giovanni;
2019

Abstract

We designed a ground-based radar system with a C-band 2-D cross multiple input multiple output (MIMO) array for 3-D imaging and displacement estimation purposes. For this system, we developed a far-field pseudo-polar image format algorithm using pseudo-polar spherical coordinate. The use of a tensor compressive sensing technique allows to focus under-sampled raw data and to optimize the data acquisition time and memory usage. A novel algorithm, named as tensor-based iterative adaptive approach, is proposed for the effective and efficient reconstruction of sparse targets with a reduced level of sidelobes. Experimental results validate the designed radar system and the proposed algorithms.
2019
Istituto Applicazioni del Calcolo ''Mauro Picone''
3-D imaging
compressive sensing (CS)
cross multiple input multiple output (MIMO)
iterative adaptive approach (IAA)
pseudo-polar spherical coordinate
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/428695
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