Research on 4-D Imaging of Holographic SAR Differential Tomography

Shuang Jin; Hui Bi; Jing Feng; Weihao Xu; Jin Xu; Jingjing Zhang

doi:10.3390/rs15133421

Remote Sensing (Jul 2023)

Research on 4-D Imaging of Holographic SAR Differential Tomography

Shuang Jin,
Hui Bi,
Jing Feng,
Weihao Xu,
Jin Xu,
Jingjing Zhang

Affiliations

Shuang Jin: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Hui Bi: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Jing Feng: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Weihao Xu: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Jin Xu: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Jingjing Zhang: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

DOI: https://doi.org/10.3390/rs15133421
Journal volume & issue: Vol. 15, no. 13
p. 3421

Abstract

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Holographic synthetic aperture radar tomography (HoloSAR) combines circular synthetic aperture radar (CSAR) and SAR tomography (TomoSAR) to enable a 360° azimuth observation of the considered scene. This imaging mode achieves a high-resolution three-dimensional (3-D) reconstruction across a full 360°. To capture the deformation information of the observed target, this paper first explores the differential HoloSAR imaging mode, which combines the technologies of CSAR and differential TomoSAR (D-TomoSAR). Then, we propose an imaging method based on the orthogonal matching pursuit (OMP) algorithm and a support generalized likelihood ratio (Sup-GLRT), aiming to achieve high-precision multi-dimensional reconstruction of the surveillance area. In addition, a statistical outlier removal (SOR) point cloud filtering technique is applied to enhance the accuracy of the reconstructed point cloud. Finally, this paper presents the detection of vehicle changes in a parking lot based on the 3-D reconstructed results.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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