Multiple objects automatic detection of GPR data based on the AC-EWV and Genetic Algorithm

• Published in: IEEE transactions on geoscience and remote sensing Vol. 61; p. 1
• Main Authors: Cui, Guangyan, Xu, Jie, Wang, Yanhui, Zhao, Shengsheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accurate Calculation of Electromagnetic Wave Velocity (AC-EWV); Algorithms; Detection; Electromagnetic radiation; Electromagnetic scattering; Entropy; F-K migration; Fitting; Genetic algorithm; Genetic algorithms; GPR; Ground penetrating radar; Hyperbolas; Machine learning algorithms; Multiple objects automatic detection; Object recognition; Pipelines; Radar; Rebar; Search problems; Searching; Voids; Wave velocity; Wavelengths
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2022.3228571

The automatic detection of multiple objects in Ground penetrating radar (GPR) data is investigated by searching for the reflected hyperbolas of buried objects, which can reduce the subjectivity of operators and improve the identification accuracy. Based on Frequency-wavenumber (F-K) migration, the accurate calculation of electromagnetic wave velocity (AC-EWV) is proposed by searching for the minimum image entropy of migrated radargrams. To avoid global searching, potential positions of object hyperbolas are selected from the binarized radargram through the vertical gray gradient searching, then the sub_window is extracted with the potential position as the center. The best fitting hyperbola is detected with the genetic algorithm (GA) in the sub_window, and objects are finally determined with five hyperbolic matching criteria and the auto-categorization. This technique is verified with the simulated and measured GPR data about rebars, pipelines, and voids, and results demonstrate that it achieves the average correct rate, average missed rate, and the average misjudged rate is 98.46 %, 1.33%, and 0.36% respectively, and the average correct rate for GPR data of the double-layer rebars is 91.67%.