NDLI: Three-dimensional inverse synthetic aperture radar imaging based on compressive sensing

Content Provider	IET Digital Library
Author	Qiu, Wei Martorella, Marco Zhou, Jianxiong Zhao, Hongzhong Fu, Qiang
Abstract	Inverse synthetic aperture radar (ISAR) can form two-dimensional (2D) electromagnetic images of a target, but it cannot provide the third dimensional information about the target. Conventional 3D turntable ISAR imaging requires data collection over densely azimuth-elevation samples, which needs a large amount of data storage. In this study, an effective 3D ISAR imaging algorithm for turntable model based on compressive sensing is proposed, which exploits the sparsity in the image domain to achieve 3D reconstruction by using a limited number of measurements. Firstly, the 3D data tensor is converted into a 2D matrix by stacking slices of data along one specific dimension; then a 2D optimisation reconstruction approach is applied to solve a sparsity-driven optimisation problem to obtain the 2D distribution of the scatterers. Lastly, 3D ISAR images are generated by rearranging the scatterer distribution in the 2D map into a 3D volume. This imaging scheme only needs a small number of measurements, and reduces the required memory and computational burden significantly. Simulation results are finally shown to validate the proposed algorithm.
Starting Page	411
Ending Page	420
Page Count	10
ISSN	17518784
Volume Number	9
e-ISSN	17518792
Issue Number	Issue 4, Apr (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/9/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2014.0260
Journal	IET Radar, Sonar & Navigation
Publisher Date	2015-04-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Map 2D Matrix Data Storage 2D Scatterer Distribution Rearrangement 2D Target Electromagnetic Image Domain 3D Data Tensor 3D Turntable ISAR Image Reconstruction Algebra Azimuth-elevation Samples Compressed Sensing Compressive Sensing Data Collection Data Stacking Slices Image And Video Coding Image Reconstruction Optimisation Optimisation Technique Radar Equipment Radar Imaging Sparse Matrix Sparsity-driven Optimisation Problem Synthetic Aperture Radar System And Application Tensors Three-dimensional Inverse Synthetic Aperture Radar Imaging Two-dimensional Electromagnetic Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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