TY - GEN
T1 - 3D ISAR Imaging
T2 - 2019 International Radar Conference, RADAR 2019
AU - Cai, Jinjian
AU - Martorella, Marco
AU - Liu, Quanhua
AU - Ding, Zegang
AU - Giusti, Elisa
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Inverse synthetic aperture radar (ISAR) is capable of producing two-dimensional (2D) and three-dimensional (3D) images of noncooperative targets. Compared to 2D ISAR images, 3D ISAR reconstruction can provide not only range and cross-range information, but also the height information of the target, which is of great significance for automatic target recognition (ATR). The alignment between the point-like 3D ISAR reconstructions of targets and the targets' models, such as CAD models, becomes one of the essential issues in ATR by 3D ISAR reconstruction. In this paper, we introduce an approach to address the proposed alignment problem. The alignment problem can be decomposed into two steps, a coarse alignment and an accurate alignment. The coarse alignment can be accomplished by means of the principal component analysis (PCA), while the accurate alignment can be achieved by iteration closest points (ICP) algorithm. In order to simulate real radar scenarios, target self-occlusion and reconstruction errors are taken into consideration. The simulation results verify the validity of the proposed methods.
AB - Inverse synthetic aperture radar (ISAR) is capable of producing two-dimensional (2D) and three-dimensional (3D) images of noncooperative targets. Compared to 2D ISAR images, 3D ISAR reconstruction can provide not only range and cross-range information, but also the height information of the target, which is of great significance for automatic target recognition (ATR). The alignment between the point-like 3D ISAR reconstructions of targets and the targets' models, such as CAD models, becomes one of the essential issues in ATR by 3D ISAR reconstruction. In this paper, we introduce an approach to address the proposed alignment problem. The alignment problem can be decomposed into two steps, a coarse alignment and an accurate alignment. The coarse alignment can be accomplished by means of the principal component analysis (PCA), while the accurate alignment can be achieved by iteration closest points (ICP) algorithm. In order to simulate real radar scenarios, target self-occlusion and reconstruction errors are taken into consideration. The simulation results verify the validity of the proposed methods.
KW - 3D ISAR reconstruction
KW - CAD model
KW - Inverse synthetic aperture radar (ISAR)
KW - iteration closest points (ICP)
KW - point cloud alignment
KW - principal component analysis (PCA)
UR - http://www.scopus.com/inward/record.url?scp=85084957678&partnerID=8YFLogxK
U2 - 10.1109/RADAR41533.2019.171419
DO - 10.1109/RADAR41533.2019.171419
M3 - Conference contribution
AN - SCOPUS:85084957678
T3 - 2019 International Radar Conference, RADAR 2019
BT - 2019 International Radar Conference, RADAR 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 September 2019 through 27 September 2019
ER -