Phase-retrieval algorithm for dual-polarization imaging in a ground-penetrating synthetic aperture radar satellite

1997 ◽  
Author(s):  
Bobby R. Hunt ◽  
Peter T. Gough
Keyword(s):  
Synthetic Aperture Radar ◽  
Phase Retrieval ◽  
Synthetic Aperture ◽  
Retrieval Algorithm ◽  
Dual Polarization ◽  
Polarization Imaging ◽  
Radar Satellite ◽  
Ground Penetrating ◽  
Phase Retrieval Algorithm ◽  
Aperture Radar

scholarly journals Non-Stationary Platform Inverse Synthetic Aperture Radar Maneuvering Target Imaging Based on Phase Retrieval

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3333 ◽  
Author(s):  
Hongyin Shi ◽  
Saixue Xia ◽  
Qi Qin ◽  
Ting Yang ◽  
Zhijun Qiao
Keyword(s):  
Synthetic Aperture Radar ◽  
Phase Retrieval ◽  
Experimental Simulation ◽  
Synthetic Aperture ◽  
Retrieval Algorithm ◽  
Imaging Method ◽  
Inverse Synthetic Aperture Radar ◽  
Maneuvering Target ◽  
Motion Parameters ◽  
Aperture Radar

As a powerful signal processing tool for imaging moving targets, placing radar on a non-stationary platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the received signal due to the instability of the radar platform, making it difficult for popular algorithms to accurately perform motion compensation, which leads to severe effects in the resultant ISAR images. Moreover, maneuvering targets may have complex motion whose motion parameters are unknown to radar systems. To overcome the issue of non-stationary platform ISAR autofocus imaging, a high-resolution imaging method based on the phase retrieval principle is proposed in this paper. Firstly, based on the spatial geometric and echo models of the ISAR maneuvering target, we can deduce that the radial motion of the radar platform or the vibration does not affect the modulus of the ISAR echo signal, which provides a theoretical basis for the phase recovery theory for the ISAR imaging. Then, we propose an oversampling smoothness (OSS) phase retrieval algorithm with prior information, namely, the phase of the blurred image obtained by the classical imaging algorithm replaces the initial random phase in the original OSS algorithm. In addition, the size of the support domain of the OSS algorithm is set with respect to the blurred target image. Experimental simulation shows that compared with classical imaging methods, the proposed method can obtain the resultant motion-compensated ISAR image without estimating the radar platform and maneuvering target motion parameters, wherein the fictitious target is perfectly focused.

scholarly journals A Framework for Correcting Ionospheric Artifacts and Atmospheric Effects to Generate High Accuracy InSAR DEM

2020 ◽  
Vol 12 (2) ◽  
pp. 318 ◽  
Author(s):  
Zhiwei Liu ◽  
Cui Zhou ◽  
Haiqiang Fu ◽  
Jianjun Zhu ◽  
Tingying Zuo
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Atmospheric Effects ◽  
Interferometric Synthetic Aperture Radar ◽  
Dual Polarization ◽  
Digital Elevation ◽  
Split Spectrum ◽  
Dem Accuracy ◽  
Study Sites ◽  
Aperture Radar

Repeat-pass interferometric synthetic aperture radar is a well-established technology for generating digital elevation models (DEMs). However, the interferogram usually has ionospheric and atmospheric effects, which reduces the DEM accuracy. In this paper, by introducing dual-polarization interferograms, a new approach is proposed to mitigate the ionospheric and atmospheric errors of the interferometric synthetic aperture radar (InSAR) data. The proposed method consists of two parts. First, the range split-spectrum method is applied to compensate for the ionospheric artifacts. Then, a multiresolution correlation analysis between dual-polarization InSAR interferograms is employed to remove the identical atmospheric phases, since the atmospheric delay is independent of SAR polarizations. The corrected interferogram can be used for DEM extraction. Validation experiments, using the ALOS-1 PALSAR interferometric pairs covering the study areas in Hawaii and Lebanon of the U.S.A., show that the proposed method can effectively reduce the ionospheric artifacts and atmospheric effects, and improve the accuracy of the InSAR-derived DEMs by 64.9% and 31.7% for the study sites in Hawaii and Lebanon of the U.S.A., respectively, compared with traditional correction methods. In addition, the assessment of the resulting DEMs also includes comparisons with the high-precision Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) altimetry data. The results show that the selection of reference data will not affect the validation results.

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