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Research on Compressive Sensing‐Based 3D Imaging Method Applied to GPR
Author(s) -
Huimin Yu,
Song Jiang
Publication year - 2013
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.28010
Subject(s) - ground penetrating radar , compressed sensing , synthetic aperture radar , computer science , aperture (computer memory) , measure (data warehouse) , point (geometry) , coded aperture , radar , algorithm , computer vision , optics , acoustics , mathematics , physics , telecommunications , data mining , geometry , detector
Results in theory of compressive sensing enable the reconstruction of sparse signals from a small set of nonadaptive linear measurements by solving a convex optimization problem. Considering the sparse structure of actual target space in ground penetrating radar (GPR) application, three‐dimensional imaging method based on random aperture compressive sensing (RACS) is brought up, which requires the GPR transceiver to record only a minimum amount of samples through incoherent measurement at each aperture point, and only to measure a small number of random apertures in x‐y plane of interested target space. Simulation and experimental results verified that the proposed RACS method allow much fewer measurement aperture points, and has much sparse imaging results with much higher resolution. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:2896–2901, 2013