International Core Journal of Engineering 2020-26 | Page 214

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Fig. 4. Simulations for normalized point source. (a) Normalized point source in Cornwell algorithm ; (b) Normalized point source in he proposed method.
Tikhonov Regularization Reconstruction Brightness
Tikhonov Regularization Reconstruction Brightness
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Fig. 5. Reconstruction Brightness; (a) Reconstruction Brightness in Cornwell algorithm ; (b) Reconstruction Brightness in UCA-MMA.
reconstruct the brightness temperature. The original scene is
shown in Fig. 6. The simulation results shows the feasibility
of proposed method.
The original two-dimensional Brightness
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IV. C ONCLUSION
In this paper, a novel modified objective function is
proposed, which uses the minimum distance of adjacent
elements as objective function and has advantages in meeting
the minimum element spacing constraint and forming a
uniform separations. Improved simulated annealing
algorithm (SA) has been applied to the proposed method.
Several comparisons of numerical results have been obtained
to demonstrate the flexibility and outperformance of this new
proposed approach.
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A CKNOWLEDGMENT
Fig. 6. Original scene.
The Author would like to thank the reviewers for their
constructive and helpful comments.
Normalized point source obtained by Cornwell algorithm
and he proposed method are shown in Fig.4. From the results,
it can be shown that for imaging the same target with the
same number of antennas, the side lobe of the point-source
image obtained by the proposed method is slightly improved.
This work was supported by the National Natural Science
Foundation of China under Grant 61671217. Corresponding
author is Xueqing Yang, School of Electronic
Informationand Communications, Huazhong University of
Science and Technology, Wuhan 430074, China.
Simulation results of reconstruction brightness of
extended source have been shown in Fig. 5. For this
simulation, the number of elements is thirty. The extended
source is a 64*64 pixel image. G matrix was used to
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