Abstract
Compressive sensing (CS) enables the reconstruction of ground-penetrating radar (GPR) signals by processing in a compressed region with a few samples instead of taking all signal samples. In this study, microwave radar signals which have been produced in microwave laboratory are processed by CS. Reflection data samples which are produced between 0.1 GHz-15 GHz frequency band with 0.074 GHz increments are taken randomly at ¼, ½, ¾ of quantity and reconstructed via convex optimization by CS. Considering the Fourier coefficients of the signals, 50 and 100 sparse Fourier coefficients are taken to analysis the difference between them.
Keywords
Compressed sensing
Ground-penetrating radar
Radar
Signal reconstruction
Radar imaging
Microwave
Fourier transform
SIGNAL (programming language)
Microwave imaging
Reflection (computer programming)
Remote sensing
Acoustics
Signal processing
Geology
Iterative reconstruction
Continuous-wave radar
Materials science
Optics
Computer science
Physics
Telecommunications
Artificial intelligence
Subject Areas
Microwave Imaging and Scattering Analysis
·Biomedical Engineering ·Physical Sciences
Sparse and Compressive Sensing Techniques
·Computational Mechanics ·Physical Sciences
Geophysical Methods and Applications
·Ocean Engineering ·Physical Sciences
Citations by Year
2016: 1
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