Integrated ground penetrating radar and DGPS method for the continuous and long-distance GPR survey in the rugged terrain

• Autorzy: Zhang Di , Gong HuiLi , Li JiaCun , Wu ZhongHai , Liu ShaoTang

Identyfikatory

DOI

10.1007/s11600-022-00751-5

• Języki publikacji: EN

Abstrakty

EN

The integrated ground penetrating radar (GPR) and global positioning system (GPS) survey has been extensively used to investigate the subsurface materials or buried-objects with the geographical information. However, when the GPR was pulled quickly, there was inadequate that the GPS signal receiver cannot real-time update its geographical coordinates by the serial com-port or USB port on the laptop. In this study, the integration of GPR and differential GPS (DGPS) was realized to acquire GPR image with the geographical information, especially for a continuous and long-distance GPR survey in the rugged terrain. When the operator with GPR system is moving on the ground surface, the pulse signals of the survey wheel were applied to trigger the GPR control unit and the GPS signal receiver at the same time. Meanwhile, the GPR data and the geographical coordinates were obtained by the GPR system and the GPS signal receiver, respectively. In addition, the time synchronization algorithm was proposed to combine each trace of the GPR image with the geographical coordinates of the GPS signal receiver. To evaluate the feasibility and efficiency of the integrated GPR and DGPS method, the 250 MHz and 500 MHz GPR profiles were performed in the four survey sites along the Litang fault. The difference between the pulse events on GPS and the GPR traces number, whether 250 MHz and 500 MHz GPR antenna, it indicates that the differences slightly increase when the distance increases on the graphs. The study results demonstrate that the integrated GPR and DGPS method has the capable of obtaining the GPR data with high-precision geographical information for a continuous and long-distance measurement in the rugged terrain. What’s more, the methodology that we introduce also offers the chance for comprehensive application of GPR data with other spatial data, such as the high-resolution remote sensing image, unmanned aerial vehicle, airborne LiDAR and so on.

Słowa kluczowe

EN

GPR; DGPS; time synchronization algorithm

PL

GPR; DGPS; algorytm synchronizacji czasu

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 2
• Strony: 537--546
• Opis fizyczny: Bibliogr. 23 poz.

Twórcy

autor

Zhang Di

• College of Resource Environment and Tourism, Capital Normal University, No. 105, Xisanhuan Road, Beijing 100048, China
• College of Civil Engineering, Henan University of Engineering, Zhengzhou 451191, China

autor

Gong HuiLi

• College of Resource Environment and Tourism, Capital Normal University, No. 105, Xisanhuan Road, Beijing 100048, China

autor

Li JiaCun

• College of Resource Environment and Tourism, Capital Normal University, No. 105, Xisanhuan Road, Beijing 100048, China

• https://orcid.org/0000-0001-7335-0755

autor

Wu ZhongHai

• Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China

autor

Liu ShaoTang

• College of Civil Engineering, Henan University of Engineering, Zhengzhou 451191, China

Bibliografia

• 1. Anchuela ÓP, Lafuente P, Arlegui L, Liesa CL, Simón J (2016) Geophysical characterization of buried active faults: the Concud Fault (Iberian Chain, NE Spain). Int J Earth Ences 105:2221–2239
• 2. Colucci RR, Forte E, Boccali C, Dossi M, Lanza L, Pipan M, Guglielmin M (2014) Evaluation of internal structure, volume and mass of glacial bodies by integrated LiDAR and ground penetrating radar surveys: the case study of canin eastern glacieret (Julian Alps, Italy). Surv Geophys 36:231–252
• 3. Cowie PA, Phillips RJ, Roberts GP, Mccaffrey K, Wilkinson M (2017) Orogen-scale uplift drives episodic behaviour of earthquake faults. Sci Reports 7
• 4. Furgale P, Barfoot TD, Ghafoor N, Williams K, Osinski G (2010) Field testing of an integrated surface/subsurface modeling technique for planetary exploration. Int J Robot Res 29:1529–1549
• 5. Jol H (2009) Ground penetrating radar: theory and applications. Elsevier Science
• 6. Karaim MO, Karama TB, Noureldin A, Tamazin M, Atia MM (2013) Real-time cycle-slip detection and correction for land vehicle navigation using inertial aiding. In: Proceedings of 26th international technical meeting of the ION satellite division, ION GNSS+ 2013, 16–20 September 2013. Institute of Navigation, Nashville, USA
• 7. Kim D, Langley RB (2001) Instantaneous real-time cycle-slip correction of dual-frequency GPS data. In: Proceedngs of international symposium on kinematic systems in geodesy, geomatics and navigation KIS 2001, 5–8 June 2001, pp 255–264. Banff, Canada
• 8. Lagüela S, Carracelas MS, Puente I, Martínez F (2018) Joint use of GPR, IRT and TLS techniques for the integral damage detection in paving. Construct Build Mater 174. https://doi.org/10.1016/j.conbuildmat.2018.04.159
• 9. Lei SG, Bian ZF (2008) Study of the integration of ground penetrating radar and 3s technology. Bull Surv Mapping
• 10. Li S, Cai H, Kamat VR (2015) Uncertainty-aware geospatial system for mapping and visualizing underground utilities. Autom Constr 53:105–119
• 11. Li SF, Li JC, Zhang D (2016) Topographic correction of GPR profiles based on differential GPS. J Geomech 771–777
• 12. Lunina OV, Gladkov AS, Gladkov AA (2019) Surface and shallow subsurface structure of the Middle Kedrovaya paleoseismic rupture zone in the Baikal Mountains from geomorphological and ground-penetrating radar investigations. Geomorphology 326:54–67
• 13. Mercedes X et al (2012) Application of non-destructive geomatic techniques and FDTD modeling to metrical analysis of stone blocks in a masonry wall—ScienceDirect. Construc Build Mater 36:14–19
• 14. Ortega-Ramírez J, Bano M, Cordero-Arce MT, Villa-Alvarado LA, Fraga CC (2020) Application of non-invasive geophysical methods (GPR and ERT) to locate the ancient foundations of the first cathedral of Puebla, Mexico. A case study. J Appl Geophys 174:103958
• 15. Puente I, Solla M, Gonzalez-Jorge H, Arias P (2013) Validation of mobile LiDAR surveying for measuring pavement layer thicknesses and volumes. NDT and E Int 60:70–76
• 16. Puente I, Solla M, Lagüela S, Sanjurjo-Pinto J (2018) Reconstructing the Roman Site “Aquis Querquennis”(Bande, Spain) from GPR, T-LiDAR and IRT data fusion. Remote Sensing 10:379
• 17. Sara R (2019) Analysis and integration of surface and subsurface information of different bridges. J Indian Soc Remote Sens
• 18. Tanajewski D, Bakula M (2016) Application of ground penetrating radar surveys and GPS surveys for monitoring the condition of levees and dykes. Acta Geophys 64:1093–1111
• 19. Viberg A, Gustafsson C, Andrén A (2020) Multi-channel ground-penetrating radar array surveys of the iron age and medieval ringfort brby on the Island of land. Remote Sensing, Sweden, p 12
• 20. Wang PY, Li ZQ, Wu LH, Li HL, Wang WB, Jin S (2012) Ice thickness and volume based on GPR, GPS and GIS: example from the Heigou glacier No.8, Bogda-Peak Region, Tianshan, China. Earth Sci 179–187
• 21. Zhang P, Sun Z, Zhang J (2007) Thickness determination of snow-ice layer on Mt. Qomolangma summit in 2005. Geomatics and Information Science of Wuhan University, pp 443–445+449
• 22. Zhang D, Li JC, Liu ST, Wang G (2019) Multi-frequencies GPR measurements for delineating the shallow subsurface features of the Yushu strike slip fault. Acta Geophysica 505–515. https://doi.org/10.1007/s11600-019-00271-9
• 23. Zhang D, Li JC, Zhao GX, Liu XY, Zhang PS, He Q (2020) An accurate location method of ground penetrating radar profiles using DGPS. Prog Geophys 35(06):2429–2434

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).