بررسی کاربرد تبدیل موجک در روش زمین-رادار با مطالعه موردی ژئوفیزیک پزشکی قانونی در محیط برف

نوع مقاله : مقاله تحقیقی‌ (پژوهشی‌)

نویسندگان

1 دانشجوی دکترای الکترومغناطیس ،موسسه ژئوفیزیک دانشگاه تهران، تهران، ایران

2 استاد گروه فیزیک زمین، موسسه ژئوفیزیک دانشگاه تهران، تهران، ایران

3 استاد گروه فیزیک زمین، دانشگاه استراسبورگ، استراسبورگ، فرانسه

چکیده

زمین- رادار (Geo-Radar) روش مناسب ژئوفیزیکی در بررسی­های نزدیک به سطح در محیط­های مختلف است و تاکنون کاربردهای فراوان آن با اهداف گوناگون مطالعه شده است. برف یکی از محیط­های کم­میرا و به‌نسبت مناسب برای مطالعات زمین- رادار است. با این حال، محیط­های برف‌گیر، چالش­ها و پیچیدگی­های خاص خود را برای مطالعات ژئوفیزیکی دارند. در بررسی روند مطالعه ژئوفیزیکی در چنین محیط­هایی، واکاوی چگونگی یافتن محل پیکر یک کوهنورد مدفون در برف به دلیل پدیده بهمن، ابعاد مختلف تحقیق کنونی را دربر­می‌گیرد. این نوع مطالعه در حیطه ژئوفیزیک قانونی (forensic geophysics) قرار می­گیرد. نخستین چالش در این‌گونه مطالعات، برخلاف ردیابی اهداف معمول، تخمین محدوده دفن کوهنورد است که باید به دقت بررسی شود. تجهیزات پوششی کوهنورد معمولاً از مواد عایق ساخته می­شود، اما بافت­های بدن نسبت به مواد نارسانا از رسانندگی الکتریکی درخور­توجهی برخوردارند. این موضوع در کنار آشفتگی­های ایجاد­شده در لایه­های مختلف برف که ناشی از بهمن است، به پیچیدگی­های این­گونه مطالعات می­افزاید. با نگاه به داده­های مطالعه موردی مدنظر، رادارگرام­های پردازش­شده ابتدایی، نشان بارزی از محل پیکر مدفون نداشتند؛ ازاین‌رو ضمن مدل­سازی پیشرو، روش­های پردازشی خاصی به‌کارگرفته شد که در نتیجه آن، تغییرات ایجاد­شده در رادارگرام­ها به‌ویژه در هنگام استفاده از تبدیل موجک پیوسته شایان توجه بود. در نهایت، با کاوش­های انجام­پذیرفته، پیکر کوهنورد فقید در عمق تقریبی یک متری یافت شد که همخوانی مناسبی با نتایج پردازش پیشرفته و تفسیر رادارگرام­ها داشت. این موضوع بیانگر آن است که رویکرد پردازشی پیشرفته در کنار پردازش­های معمول می­تواند نتایج مناسبی برای تفسیر داده­ها فراهم کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigation of the application of wavelet transform to Geo-Radar with a case study of forensic geophysics in snow

نویسندگان [English]

  • sajjad Ghanbari 1
  • mohamad kazem Hafizi 2
  • Maksim Bano 3
1 Ph.D Student, Institute of geophysics, University of Tehran, Tehran, Iran
2 Professor, Institute of geophysics, University of Tehran, Tehran, Iran
3 Associate Professor, Ecole et Observatoire, Université de Strasbourg, Strasbourg, France
چکیده [English]

Geophysical techniques have been successfully used by law enforcement agencies to locate graves and forensic evidences. Nonetheless, more controlled research is needed to better understand the applicability of this technology. Ground-Penetrating Radar (GPR) is a non-invasive geophysical method that uses radar pulses to image the subsurface. This method can be used in a variety of media, including rock, soil, ice, fresh water, pavements and structures. Different applications of GPR as a convenient geophysical tool have been studied in near-surface assessments for diverse media and targets. Snow is one of the low-loss medium and relatively suitable for GPR studies. Considering geophysical approaches in such environments, we will deliberate how body of a mountain climber was detected in snow due to avalanche occurrence. This kind of study is part of forensic geophysics. First step in such works is to estimate the position of the buried body by inspecting the place cautiously, which is different than routine works. Important points that assist in such cases are avalanche path, and rocks/hills and obstacles in the way after avalanche incident to mountaineer which react as a trap. Against the mountaineer body’s coverings which are formed by non-conductive materials, the body involves highly conductive textures. This phenomenon along with turbulences in snow layers occurred by the avalanche, increase complexity of these kind of studies. However, for investigation in places without avalanche incident and with more homogenous target, the procedure is simpler and straight forward. Looking at the data of mentioned in the case study, initially processed radargrams have no obvious sign of the buried body. Building a synthetic model based on environment and target properties can provide better vision for processing procedure. Therefore, besides forward modelling, some advanced methods were used. The applied advanced process created remarkable changes in radargrams especially when continuous wavelet transform (CWT) is used. It seems that application of some processing parameters leads to higher amplitudes in radargrams. Eventually, more apparent hyperbola related to the target, were appeared that helped to separate snowy layer from beneath rock. In this direction, excavation a trench and laying a survey inside of it which was a convenient place to conduct data acquisition, was helpful to find probable indications to mountaineer’s body location. At the end, excavations revealed the body of climber at the depth around 1m where substantiated the results achieved from advanced processes and interpreted radargrams. Overall, advanced processing approach along with commonly used processes can reap suitable results for data interpretation.

کلیدواژه‌ها [English]

  • CWT
  • GPR
  • Forensic Geophysics
  • Signal processing
  • Snow
قنبری، س.، حفیظی، م.، 1392، بررسی اثر بسامد مرکزی آنتن و کاربرد پارامترهای پردازشی در مکان­یابی تأسیسات شهری مدفون به روش GPR: مجله ژئوفیزیک ایران، 7(3)، 93-106.
قنبری، س.، حفیظی، م.، 1395، کاربرد مدل­سازی پیشرو و الگوریتم پردازشی مناسب در تعیین محل قنات به روش GPR: مجله ژئوفیزیک ایران،١٠(2)، 67-82.
محمدی ویژه، م.، کامکارروحانی، ا، 1390، بررسی ساختارهای مدفون نزدیک سطح زمین با استفاده از روش­های GPR و مقاومت ویژه: یک مطالعه موردی: مجله علوم زمین، 80،‎ 163-170.
Abduljabbar, A., Yavuz, M. E., Costen, F., Himeno, R., and Yokota, H., 2017, Continuous wavelet transform based frequency dispersion compensation method for electromagnetic time-reversal imaging: IEEE Transactions on Antennas and Propagation, 65(3), 1321-1329.
Amran, T. S. T., Amin, M. S. M., Ahmad, M. R., Sani, S., Masenwat, N. A., Abas, A. A., ... , and Adnan, M. A. K., 2020, Ground Penetrating Radar (GPR) applications in forensic: Jurnal Sains Nuklear Malaysia, 32(1), 49-57.
Annan, A. P., and Cosway, S. W., 1992, Ground penetrating radar survey design: 5th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems (pp. cp-210), European Association of Geoscientists & Engineers.
Annan, A. P., Diamanti, N., Redman, J. D., and Jackson, S. R., 2016, Ground-penetrating radar for assessing winter roads: Geophysics, 81(1), WA101-WA109.
Arft, C. M., & Knoesen, A. (2004). An efficient finite‐difference frequency‐domain method including thin layers. Microwave and Optical Technology Letters, 43(1), 40-44.
Arslan, A. N., Wang, H., Pulliainen, J., and Hallikainen, M., 2001, Effective permittivity of wet snow using strong fluctuation theory: Progress in Electromagnetics Research, 31, 273-290.
Baili, J., Lahouar, S., Hergli, M., Al-Qadi, I. L., and Besbes, K., 2009, GPR signal de-noising by discrete wavelet transform: NDT & E International, 42(8), 696-703.
Bano, M. (1996). Constant dielectric losses of ground-penetrating radar waves. Geophysical Journal International, 124(1), 279-288.
Barone, P. M., and Di Maggio, R. M., 2018, Forensic investigations of geohazards: the Norcia 2016 earthquake: Geosciences, 8(9), 316.
Barone, P. M., and Di Maggio, R. M., 2019, Forensic geophysics: ground penetrating radar (GPR) techniques and missing person's investigations: Forensic Sciences Research, 4(4), 337-340.
Bitri, A., & Grandjean, G. (2008). Frequency–wavenumber modelling and migration of 2D GPR data in moderately heterogeneous dispersive media [Link]. Geophysical Prospecting, 46(3), 287-301.
Bradford, J. H., and Harper, J. T., 2005, Wave field migration as a tool for estimating spatially continuous radar velocity and water content in glaciers: Geophysical Research Letters, 32(8).
Bradford, J. H., Harper, J. T., and Brown, J., 2009, Complex dielectric permittivity measurements from ground‐penetrating radar data to estimate snow liquid water content in the pendular regime: Water Resources Research, 45(8).
Canata, R. E., Ferreira, F. J. F., Borges, W. R., and
 
da Silva Salvador, F. A., 2020, Analysis of 2D and 3D GPR responses in the Federal University of Paraná Forensic Geophysics Controlled Site – a case study: Revista Brasileira de Geofisica, 38(2).
Cheng, W., and Hirakawa, K., 2015, Minimum risk wavelet shrinkage operator for Poisson image denoising: IEEE Transactions on Image Processing, 24(5), 1660-1671.
Chen, H. W., & Huang, T. M. (1998). Finite-difference time-domain simulation of GPR data. Journal of Applied Geophysics, 40(1-3), 139-163.
Colbeck, S. C., 1997, A review of sintering in seasonal snow: CRREL Report 97-10, Hanover NH, US Army Cold Regions Research and Engineering Laboratory, 17 pp.
Damiata, B. N., Walker, J., Stansell, A., and Steinberg, J. M., 2020, On GPR surveying of historical cemeteries and ancient graveyards to aid forensic research: 18th International Conference on Ground Penetrating Radar, Society of Exploration Geophysicists, Colorado, 14-19 June 2020.
Daniels, D. J., 2005, Ground penetrating radar: Encyclopedia of RF and microwave engineering.
Daniels, D. J., 2007, Ground Penetrating Radar, 2nd edition: The Institution of Engineering and Technology.
Davenport, G. C., 2001, Where is it? Searching for buried bodies and hidden evidence: SportWork, Church Hill, MD.
Davis, J. L., and Anann, A. P., 1989, Ground‐penetrating radar for high‐resolution mapping of soil and rock stratigraphy: Geophysical Prospecting, 37(5), 531-551.
Dupras, T. L., Schultz, J. J., Wheeler, S. M., and Williams, L. J., 2011, Forensic recovery of human remains: Archaeological Approaches, CRC Press.
Ebrahimi, A., Ghanbari, S., and Ashtari, A., 2012, FDTD numerical GPR stratigraphy modeling and processing and a case study with GPR data: Society of Exploration Geophysicists and The Chamber of Geophysical Engineers of Turkey, 1-4.
Ebrahimi, A., Gholami, A., and Nabi-Bidhendi, M., 2017, Sparsity-based GPR blind deconvolution and wavelet estimation: Journal of Indian Geophysical Union, 21(1), 7-12.
Farge, M., 1992, Wavelet transforms and their applications to turbulence: Annual Review of Fluid Mechanics, 24(1), 395-458.
Forbes, S. L., Hulsman, S., and Dolderman, M., 2013, Locating buried canine remains using ground penetrating radar: Canadian Society of Forensic Science Journal, 46(1), 51-58.
Fujita, S., Matsuoka, T., Ishida, T., Matsuoka, K., and Mae, S., 2000, A summary of the complex dielectric permittivity of ice in the megahertz range and its applications for radar sounding of polar ice sheets, in Physics of Ice Core Records (pp. 185-212), Hokkaido University Press.
Gabriel, C., Gabriel, S., and Corthout, Y. E., 1996, The dielectric properties of biological tissues: I. Literature survey: Computer Science, Medicine, Physics in Medicine and Biology, 41(11), 2231.
Galley, R. J., Trachtenberg, M., Langlois, A., Barber, D. G., and Shafai, L., 2009, Observations of geophysical and dielectric properties and ground penetrating radar signatures for discrimination of snow, sea ice and freshwater ice thickness: Cold Regions Science and Technology, 57(1), 29-38.
Greene, E., Birkeland, K. W., Elder, K., Johnson, G., Landry, C., McCammon, I., ... , and Williams, K., 2004, Snow, weather, and avalanches: Observational guidelines for avalanche programs in the United States, American Avalanche Association, Pagosa Springs, Colorado, 150.
Hammon III, W. S., McMechan, G. A., and Zeng, X., 2000, Forensic GPR: finite-difference simulations of responses from buried human remains: Journal of Applied Geophysics, 45(3), 171-186.
Holoborodko, P., 2008, Smooth noise robust differentiators: Consulted on, 7(2008), 2015.
Javadi, M., and Ghasemzadeh, H., 2017, Wavelet analysis for ground penetrating radar applications: A case study: Journal of Geophysics and Engineering, 14(5), 1189-1202.
Khaidukov, V., Landa, E., and Moser, T. J., 2004, Diffraction imaging by focusing-defocusing: An outlook on seismic superresolution: Geophysics, 69(6), 1478-1490.
Khan, U. S., and Al-Nuaimy, W., 2010, Background removal from GPR data using eigenvalues, in Proceedings of the XIII Internarional Conference on Ground Penetrating Radar, IEEE, 1-5.
Killam, E. W., 2004, The detection of human remains: Charles C. Thomas Publisher.
Marshall, H. P., Koh, G., and Forster, R. R., 2005, Estimating alpine snowpack properties using FMCW radar: Annals of Glaciology, 40, 157-162.
Mellett, J. S., 1992, Location of human remains with ground-penetrating radar, in Fourth International Conference on Ground Penetrating Radar (pp. cp-303), European Association of Geoscientists and Engineers.
Mohana, M. A., Abbas, A. M., Gomaa, M. L., and Ebrahim, S. M., 2013, Discrimination between landmine and mine-like targets using wavelets and spectral analysis: NRIAG Journal of Astronomy and Geophysics, 2(1), 54-66.
Morlet, J., Arens, G., Fourgeau, E., and Glard, D., 1982, Wave propagation and sampling theory—Part I: Complex signal and scattering in multilayered media: Geophysics, 47(2), 203-221.
Neal, A., 2004, Ground-penetrating radar and its use in sedimentology: principles, problems and progress: Earth-Science Reviews, 66(3-4), 261-330.
Pethig, R., 1985, Dielectric and electrical properties of biological materials: Journal of Bioelectricity, 4(2), vii-ix.
Plonka, G., Tenorth, S., and Rosca, D., 2010, A new hybrid method for image approximation using the easy path wavelet transform: IEEE Transactions on Image Processing, 20(2), 372-381.
Pye, K., and Croft, D. J., (Eds.), 2004, Forensic geoscience: principles, techniques and applications: Geological Society of London.
Quellec, G., Lamard, M., Cazuguel, G., Cochener, B., and Roux, C., 2009, Adaptive nonseparable wavelet transform via lifting and its application to content-based image retrieval: IEEE Transactions on Image Processing, 19(1), 25-35.
Radzevicius, S. J., Guy, E. D., and Daniels, J. J., 2000, Pitfalls in GPR data interpretation: differentiating stratigraphy and buried objects from periodic antenna and target effects: Geophysical Research Letters, 27(20), 3393-3396.
Ruffell, A., Donnelly, C., Carver, N., Murphy, E., Murray, E., and McCambridge, J., 2009, Suspect burial excavation procedure: a cautionary tale: Forensic Science International, 183(1-3), e11-e16.
Schultz, J. J., 2007, Using ground-penetrating radar to locate clandestine graves of homicide victims: forming forensic archaeology partnerships with law enforcement: Homicide Studies, 11(1), 15-29.
Schwan, H. P., and Li, K., 1953, Capacity and conductivity of body tissues at ultrahigh frequencies: Proceedings of the IRE, 41(12), 1735-1740.
Sensors and software, 1999, Ground Penetrating Radar, Survey Design: Sensor & Softwate Inc.
Sensors and software, 1999, Pulse EKKO 100 RUN User’s Guide, Version 1.2: Sensor & Softwate Inc.
Sensors and software, 1999, Win_EKKO User’s Guide, Version 1.0: Sensor & Softwate Inc.
Sharma, P., Kumar, B., Singh, D., & Gaba, S. P. (2017). Critical Analysis of Background Subtraction Techniques on Real GPR Data. Defence Science Journal, 67(5).
Sihvola, A., and Tiuri, M., 1986, Snow fork for field determination of the density and wetness profiles of a snow pack:. IEEE Transactions on Geoscience and Remote Sensing, 5, 717-721.
Sun, M., Pan, J., Le Bastard, C., Wang, Y., and Li, J., 2019, Advanced signal processing methods for ground-penetrating radar: Applications to civil engineering: IEEE Signal Processing Magazine, 36(4), 74-84.
Taflove, A., and Hagness, S. C., 1995, Computational Electrodynamics: the Tinite-Difference Time-Domain Method: Artech House, Boston, 149-161.
Tiuri, M., Sihvola, A., Nyfors, E. G., and Hallikaiken, M., 1984, The complex dielectric constant of snow at microwave frequencies: IEEE Journal of oceanic Engineering, 9(5), 377-382.
Torrence, C., and Compo, G. P., 1998, A practical guide to wavelet analysis: Bulletin of the American Meteorological Society, 79(1), 61-78.
Tzanis, A., 2010, matGPR Release 2: A freeware MATLAB® package for the analysis and interpretation of common and single offset GPR data: FastTimes, 15(1), 17-43.
Ulaby, F. T., Michielssen, E., and Ravaioli, U., 2010, Fundamentals of applied electromagnetics: Prentice Hall.
Van Overmeeren, R. A., 1994, Georadar for hydrogeology: First Break, 12(8).
Yavuz, M. E., Fouda, A. E., and Teixeira, F. L., 2014, GPR signal enhancement using sliding-window space-frequency matrices: Progress in Electromagnetics Research, 145, 1-10.
Yavuz, M. E., & Teixeira, F. L. (2009). Ultrawideband microwave sensing and imaging using time-reversal techniques: A review. Remote Sensing, 1(3), 466-495.
Yilmaz, O., 1987, Seismic Data Processing, edited by S. M. Doherty: Society of Exploration Geophysics, Tulsa, Okla.
Zheng, J., Peng, S. P., and Yang, F., 2014, A novel edge detection for buried target extraction after SVD-2D wavelet processing: Journal of Applied Geophysics, 106, 106-113.