Application and Improvement of Phase Gradient Autofocus Algorithm in Synthetic Aperture Lidar

2016 ◽  
Vol 53 (6) ◽  
pp. 062801
Author(s):  
张洁 Zhang Jie ◽  
王然 Wang Ran ◽  
张珂殊 Zhang Keshu
2021 ◽  
Vol 13 (15) ◽  
pp. 2916
Author(s):  
Faguang Chang ◽  
Dexin Li ◽  
Zhen Dong ◽  
Yang Huang ◽  
Zhihua He

Due to the high altitude of geosynchronous synthetic aperture radar (GEO SAR), its synthetic aperture time can reach up to several hundred seconds, and its revisit cycle is very short, which makes it of great application worth in the remote sensing field, such as in disaster monitoring and vegetation measurements. However, because of the elevation of the target, elevation spatial variation error is caused in the GEO SAR imaging. In this paper, we focus on the compensation of the elevation space-variant error in the fast variant part with the autofocus method and utilize the error to carry out elevation inversing in complex scenes. For a complex scene, it can be broken down into a slow variant slope and the remaining fast variant part. First, the phase error caused by the elevation spatial variation is analyzed. Second, the spatial variant error caused by the slowly variant slope is compensated with the improved imaging algorithm. The error caused by the remaining fast variable part is the focus of this paper. We propose a block map-drift phase gradient autofocus (block-MD-PGA) algorithm to compensate for the random phase error part. By dividing sub-blocks reasonably, the elevation spatial variant error is compensated for by an autofocus algorithm in each sub-block. Because the errors of different elevations are diverse, the proposed algorithm is suitable for the scene where the target elevations are almost the same after the sub-blocks are divided. Third, the phase error obtained by the autofocus method is used to inverse the target elevation. Finally, simulations with dot-matrix targets and targets based on the high-resolution TerraSAR-X image verify the excellent effect of the proposed method and the accuracy of the elevation inversion.


2009 ◽  
Author(s):  
Phillip Gatt ◽  
Don Jacob ◽  
Bert Bradford ◽  
Joe Marron ◽  
Brian Krause

2020 ◽  
Author(s):  
Vasily Matkivsky ◽  
Alexander Moiseev ◽  
Pavel Shilyagin ◽  
Alexander Rodionov ◽  
Hendrik Spahr ◽  
...  

A method for numerical estimation and correction of aberrations of the eye in fundus imaging with optical coherence tomography (OCT) is presented. Aberrations are determined statistically by using the estimate based on likelihood function maximization. The method can be considered as an extension of the phase gradient autofocusing algorithm in synthetic aperture radar imaging to 2D optical aberrations correction. The efficiency of the proposed method has been demonstrated in OCT fundus imaging with 6λ aberrations. After correction, single photoreceptors were resolved. It is also shown that wavefront distortions with high spatial frequencies can be determined and corrected.Graphical Abstract for Table of Contents[Text. This work is dedicated to development a method for numerical estimation and correction of aberrations of the eye in fundus imaging with OCT. Aberration evaluation is performed statistically by using estimate based on likelihood function maximization. The efficiency of the proposed method has been demonstrated in OCT fundus imaging with 6λ aberrations. It has been shown that spatial high-frequency wavefront distortions can be determined]


2015 ◽  
Vol 9 (7) ◽  
pp. 900-906 ◽  
Author(s):  
Peng Shao ◽  
Mengdao Xing ◽  
Xiang‐Gen Xia ◽  
Yachao Li ◽  
Xueshi Li ◽  
...  

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