MT-BCS-Based Two-Dimensional Diffraction Tomographic GPR Imaging Algorithm With Multiview-Multistatic Configuration

• Published in: IEEE geoscience and remote sensing letters Vol. 13; no. 6; pp. 831 - 835
• Main Authors: Sun, Yanpeng, Qu, Lele, Zhang, Shi, Yin, Yuqing
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-06-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna measurements; Diffraction; Diffraction tomographic (DT); Frequency domains; Frequency measurement; Ground penetrating radar; ground penetrating radar (GPR); Image reconstruction; Imaging; Mathematical models; multitask Bayesian compressive sensing (MT-BCS); multiview-multistatic; Radar imaging; Tomography; multitask Bayesian compressive sensing (MT-BCS); Diffraction tomographic (DT); multiview–multistatic; ground penetrating radar (GPR)
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2016.2549538

High-resolution ground-penetrating radar multiview-multistatic diffraction-tomographic (DT) imaging usually requires the wide signal bandwidth and large antenna aperture, which results in the great amount of imaging data. To solve the aforementioned problem, an innovative 2-D multiview-multistatic DT imaging algorithm based on the multitask Bayesian compressive sensing (MT-BCS) strategy is proposed in this letter. The reduction of the measurement data can be achieved by performing a reduced set of measurements in the frequency domain. In particular, a joint Bayesian sparse reconstruction scheme is used to recover the original frequency domain data from the reduced frequency measurements across all the measurement positions. Finally, the image of the investigation domain can be reconstructed by the traditional multiview-multistatic DT imaging algorithm. Numerical simulation results have shown that the proposed imaging method can not only reduce the frequency measurement data but also provide the satisfactory quality of the reconstructed image.