scholarly journals Joint Optimization of System Design and Reconstruction in MIMO Radar Imaging

2021 ◽  
Author(s):  
Tomer Weiss ◽  
Nissim Peretz ◽  
Sanketh Vedula ◽  
Arie Feuer ◽  
Alex Bronstein
Keyword(s):  
System Design ◽  
Radar Imaging ◽  
Mimo Radar ◽  
Joint Optimization

Sparsity-based MIMO radar imaging method

2011 ◽  
Author(s):  
Dang-Wei Wang ◽  
A-Lei Chen ◽  
Jun- Quan Yuan ◽  
Xiao-Yan Ma
Keyword(s):  
Radar Imaging ◽  
Mimo Radar ◽  
Imaging Method

Iterative Adaptive Approaches to MIMO Radar Imaging

2010 ◽  
Vol 4 (1) ◽  
pp. 5-20 ◽  
Author(s):  
William Roberts ◽  
Petre Stoica ◽  
Jian Li ◽  
Tarik Yardibi ◽  
Firooz A. Sadjadi
Keyword(s):  
Radar Imaging ◽  
Mimo Radar ◽  
Adaptive Approaches

scholarly journals Joint Optimization Method of Airborne MIMO Radar Track and Radiated Power Based on Mutual Information

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 136278-136295
Author(s):  
Xiangyu Fan ◽  
Peng Bai ◽  
Hongwei Wang ◽  
Jiaqiang Zhang ◽  
Huanyu Li
Keyword(s):  
Mutual Information ◽  
Optimization Method ◽  
Mimo Radar ◽  
Joint Optimization ◽  
Radiated Power

scholarly journals An Imaging Plane Calibration Method for MIMO Radar Imaging

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5261
Author(s):  
Yuanyue Guo ◽  
Bo Yuan ◽  
Zhaohui Wang ◽  
Rui Xia
Keyword(s):  
Multiple Input Multiple Output ◽  
Calibration Method ◽  
Radar Imaging ◽  
Spatial Spectrum ◽  
Mimo Radar ◽  
Cooperative Movement ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Calibration Algorithm ◽  
Imaging Plane

In two dimensional cross-range multiple-input multiple-output radar imaging for aerial targets, due to the non-cooperative movement of the targets, the estimated imaging plane parameters, namely the center and the posture angles of the imaging plane, may have deviations from true values, which defocus the final image. This problem is called imaging plane mismatch in this paper. Focusing on this problem, firstly the deviations of spatial spectrum fulfilling region caused by imaging plane mismatch is analyzed, as well as the errors of the corresponding spatial spectral values. Thereupon, the calibration operation is deduced when the imaging plane parameters are accurately obtained. Afterwards, an imaging plane calibration algorithm is proposed to utilize particle swarm optimization to search out the imaging plane parameters. Finally, it is demonstrated through simulations that the proposed algorithm can accurately estimate the imaging plane parameters and achieve good image focusing performance.

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