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Journal articles on the topic 'Buried objects'

Author: Grafiati

Published: 25 January 2025

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1

Liu, Guoqin, Vyacheslav Aranchuk, Likun Zhang, and Craig J. Hickey. "Laser-acoustic detection of objects buried underwater." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A53. http://dx.doi.org/10.1121/10.0018138.

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An object buried underwater such as landmines can potentially be excited to vibrate by a sound source in air. The vibration then radiates a secondary wave in the water to excite the water surface vibration which can be detected by a laser sensor. This idea of laser-acoustic detection of buried objects is effective in detecting objects buried under ground where the object is mechanically excited and the ground surface vibration is scanned by the laser sensor. When applying this approach to detect objects buried underwater, the addition of the water layer has an impact on the flexibility of the detection. Numerical simulations and laboratory experiments are conducted to assess this flexibility. Vibrations of the object and the water surface are experimentally measured and numerically simulated for water layers of different depths. The results reveal the impact of the water layer and the effectiveness of the detection. [Work supported by the Office of Naval Research under Award No. N00014-21-1-2247.]

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2

Lim, Raymond, and Roger H. Hackman. "Acoustic interactions with buried objects." Journal of the Acoustical Society of America 86, S1 (November 1989): S4. http://dx.doi.org/10.1121/1.2027536.

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3

Guo, Yanping, Harvey W. Ko, and David M. White. "3-D localization of buried objects by nearfield electromagnetic holography." GEOPHYSICS 63, no. 3 (May 1998): 880–89. http://dx.doi.org/10.1190/1.1444398.

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We present a practical method of localizing underground objects with low‐frequency electromagnetic fields. The method uses spatial information from the field measured on the ground, and a nearfield “holographic” theory to reconstruct the field image of buried objects. Both numerical simulations and field tests demonstrate that buried metallic objects can be resolved and individually localized in 3-D space even if the measurement field shows only a single peak as might be indicative of a single object.

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4

Syambas, Nana Rachmana. "An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System." International Journal of Antennas and Propagation 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/919741.

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Surface ground-penetrating radar (GPR) is one of the radar technology that is widely used in many applications. It is nondestructive remote sensing method to detect underground buried objects. However, the output target is only hyperbolic representation. This research develops a system to identify a buried object on surface GPR based on decision tree method. GPR data of many basic objects (with circular, triangular, and rectangular cross-section) are classified and extracted to generate data training model as a unique template for each type of basic object. The pattern of object under test will be known by comparing its data with the training data using a decision tree method. A simple powerful algorithm to extract feature parameters of object which is based on linear extrapolation is proposed. The result showed that tested buried basic objects can be correctly predicted and the developed system works properly.

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5

Cong, Weihua, and Lisheng Zhou. "Three dimensional acoustic imaging technology of buried object detection." MATEC Web of Conferences 283 (2019): 04010. http://dx.doi.org/10.1051/matecconf/201928304010.

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With the development of 21th century seabed imaging sonar technology, more and more attention is paid to buried object detection technology in the world. In this paper, a low frequency and high resolution three-dimensional acoustic imaging of buried object detection method and its application example are given. Compared with the traditional two-dimensional synthetic aperture imaging, the 3D imaging technology not only solves the problem of the aliasing of the seabed formation echo and the sea floor echo, being able to provide the target buried depth, but also the 3D imaging is more helpful to the image recognition. The 3D acoustic imaging method proposed by this paper has already become the development trend of buried object detection technology. We have noticed that, different from the three-dimensional visualization of the target in the water, the three-dimensional visualization of buried objects has a serious formation image occlusion problem. In addition, the three-dimensional imaging needs to be obtained centimeter-level resolution on three dimensions for better image recognition of small buried objects, in which azimuth resolution is the bottleneck.

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6

Barrows, Larry, and Judith E. Rocchio. "Magnetic Surveying for Buried Metallic Objects." Groundwater Monitoring & Remediation 10, no. 3 (August 1990): 204–11. http://dx.doi.org/10.1111/j.1745-6592.1990.tb00016.x.

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7

Morrow, I. L., and P. van Genderen. "Effective imaging of buried dielectric objects." IEEE Transactions on Geoscience and Remote Sensing 40, no. 4 (April 2002): 943–49. http://dx.doi.org/10.1109/tgrs.2002.1006383.

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8

McCann, Bill, and Paul Mackie. "Physics helps to find buried objects." Physics World 10, no. 9 (September 1997): 24. http://dx.doi.org/10.1088/2058-7058/10/9/17.

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9

Baussard, Alexandre, Eric L. Miller, and Dominique Lesselier. "Adaptive multiscale reconstruction of buried objects." Inverse Problems 20, no. 6 (November 9, 2004): S1—S15. http://dx.doi.org/10.1088/0266-5611/20/6/s01.

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10

Sessarego, Jean P., and Jean Sageloli. "Detection of buried objects: Tank experiments." Journal of the Acoustical Society of America 104, no. 3 (September 1998): 1782–83. http://dx.doi.org/10.1121/1.424147.

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11

Sullivan, Edmund J., and Ning Xiang. "Model‐based detection of buried objects." Journal of the Acoustical Society of America 127, no. 3 (March 2010): 2026. http://dx.doi.org/10.1121/1.3385307.

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12

Ukaegbu, Ikechukwu K., Kelum A. A. Gamage, and Michael D. Aspinall. "Integration of Ground- Penetrating Radar and Gamma-Ray Detectors for Nonintrusive Characterisation of Buried Radioactive Objects." Sensors 19, no. 12 (June 18, 2019): 2743. http://dx.doi.org/10.3390/s19122743.

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The characterisation of buried radioactive wastes is challenging because they are not readily accessible. Therefore, this study reports on the development of a method for integrating ground-penetrating radar (GPR) and gamma-ray detector measurements for nonintrusive characterisation of buried radioactive objects. The method makes use of the density relationship between soil permittivity models and the flux measured by gamma ray detectors to estimate the soil density, depth and radius of a disk-shaped buried radioactive object simultaneously. The method was validated using numerical simulations with experimentally-validated gamma-ray detector and GPR antenna models. The results showed that the method can simultaneously retrieve the soil density, depth and radius of disk-shaped radioactive objects buried in soil of varying conditions with a relative error of less than 10%. This result will enable the development of an integrated GPR and gamma ray detector tool for rapid characterisation of buried radioactive objects encountered during monitoring and decontamination of nuclear sites and facilities.

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13

Karle, N., M. Boldt, A. Thiele, and U. Thoennessen. "3D MAPPING OF BURIED PIPES IN MULTI-CHANNEL GPR DATA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2022 (May 30, 2022): 85–91. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2022-85-2022.

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Abstract. Ground Penetrating Radar (GPR) allows a non-destructive analysis of the subsurface by using electromagnetic waves. GPR is used in application fields such as archeology and civil engineering, where the detection of buried objects is in demand. Such objects, e.g. pipes, lead to a disturbance of the propagation of the radar signal in the underground. A manual detection of disturbing objects can be both time-consuming and tedious, depending on the number of GPR images to be investigated. Hence, automatic methods should be considered. In this study, an object-oriented image analysis approach for the automatic detection and mapping of buried pipes is presented and evaluated. As dataset, measurements of the multi-channel system Stream C are considered.

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14

Siebauer, Christian, and Heyno Garbe. "3D Contour Shaping of Buried Objects in Soil." Advances in Radio Science 19 (December 17, 2021): 173–78. http://dx.doi.org/10.5194/ars-19-173-2021.

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Abstract. The basic question of this paper was, whether a detected anomaly found in the ground during an explosives disposal process is actually a non-detonated bomb or non-dangerous metallic scrap. Based on a borehole radar, an approach is to be presented in which first a 2-dimensional contour of the object is created with the aid of a spatial runtime evaluation. By repeating this step at different depths with subsequent graphic overlay, a 3D shape of the buried object is created. The method is first tested using a simulation model with inhomogeneous soil. In the second step the method will be applied and evaluated using a field measurement of a real object. The results shows that both 2D and 3D evaluations reflect the position and orientation of the object. Furthermore, the shape and the dimensions can be estimated, with the restriction that the 3D contour has distortions along the vertical axis. The aim of this work is to show an application of borehole radar, with which the identification of buried objects should be facilitated.

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15

Don, Charles G., David E. Lawrence, and Andrew J. Rogers. "Using acoustic impulses to detect buried objects." Journal of the Acoustical Society of America 103, no. 5 (May 1998): 2950. http://dx.doi.org/10.1121/1.422236.

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16

Kozaczka, Eugeniusz. "Parametric sonars in searching of buried objects." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3754. http://dx.doi.org/10.1121/1.2935323.

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17

Schock, Steven. "Imaging buried objects using synthetic aperture processing." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3900. http://dx.doi.org/10.1121/1.2935872.

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18

Bourennane, Salah. "Array processing methods for identifying buried objects." Journal of the Acoustical Society of America 115, no. 5 (May 2004): 2547. http://dx.doi.org/10.1121/1.4783714.

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19

Frazier, Catherine H., Nail Çadallı, David C. Munson, and William D. O’Brien. "Acoustic imaging of objects buried in soil." Journal of the Acoustical Society of America 108, no. 1 (July 2000): 147–56. http://dx.doi.org/10.1121/1.429451.

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20

Young-Jin Park, Kwan-Ho Kim, Sung-Bae Cho, Dong-Wook Yoo, Dong-Gi Youn, and Young-Kyung Jeong. "Buried small objects detected by UWB GPR." IEEE Aerospace and Electronic Systems Magazine 19, no. 10 (October 2004): 3–6. http://dx.doi.org/10.1109/maes.2004.1365009.

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21

Hill, D. A. "Near-field detection of buried dielectric objects." IEEE Transactions on Geoscience and Remote Sensing 27, no. 4 (July 1989): 364–68. http://dx.doi.org/10.1109/36.29555.

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22

Tetik, Evrim, and Ibrahim Akduman. "3D Imaging of Dielectric Objects Buried under a Rough Surface by Using CSI." International Journal of Antennas and Propagation 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/179304.

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A 3D scalar electromagnetic imaging of dielectric objects buried under a rough surface is presented. The problem has been treated as a 3D scalar problem for computational simplicity as a first step to the 3D vector problem. The complexity of the background in which the object is buried is simplified by obtaining Green’s function of its background, which consists of two homogeneous half-spaces, and a rough interface between them, by using Buried Object Approach (BOA). Green’s function of the two-part space with planar interface is obtained to be used in the process. Reconstruction of the location, shape, and constitutive parameters of the objects is achieved by Contrast Source Inversion (CSI) method with conjugate gradient. The scattered field data that is used in the inverse problem is obtained via both Method of Moments (MoM) and Comsol Multiphysics pressure acoustics model.

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23

Carpio, Ana, and María-Luisa Rapún. "Multifrequency Topological Derivative Approach to Inverse Scattering Problems in Attenuating Media." Symmetry 13, no. 9 (September 15, 2021): 1702. http://dx.doi.org/10.3390/sym13091702.

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Detecting objects hidden in a medium is an inverse problem. Given data recorded at detectors when sources emit waves that interact with the medium, we aim to find objects that would generate similar data in the presence of the same waves. In opposition, the associated forward problem describes the evolution of the waves in the presence of known objects. This gives a symmetry relation: if the true objects (the desired solution of the inverse problem) were considered for solving the forward problem, then the recorded data should be returned. In this paper, we develop a topological derivative-based multifrequency iterative algorithm to reconstruct objects buried in attenuating media with limited aperture data. We demonstrate the method on half-space configurations, which can be related to problems set in the whole space by symmetry. One-step implementations of the algorithm provide initial approximations, which are improved in a few iterations. We can locate object components of sizes smaller than the main components, or buried deeper inside. However, attenuation effects hinder object detection depending on the size and depth for fixed ranges of frequencies.

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24

Helaly, A., L. Shafai, and A. Sebak. "Low-frequency response of a buried object in a lossy ground." Canadian Journal of Physics 68, no. 1 (January 1, 1990): 111–20. http://dx.doi.org/10.1139/p90-017.

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An approximate method is developed for treating problems of electromagnetic scattering, at low frequencies, from a buried object in a lossy ground and excited by a source located in the air region above. The field incident on the object's surface is calculated using the dyadic Green's functions for a half-space. Neglecting the coupling between the air–Earth interface and the object as a first-order approximation at low frequencies, we formulate the scattering problem in terms of the magnetic-field integral equation in conjunction with the impedance boundary conditions. The method of moments is then used to reduce the magnetic-field integral equation to a matrix one in order to determine the induced surface currents. The total scattered field is separated into two terms. One is the direct scattered field, which acts as if no buried inhomogeneity were present. The other term is the anomalous field, which represents the presence of the inhomogeneity. Solutions have been generated, and the numerical results are examined for a few limiting cases to confirm their accuracy. The formulation is then applied for investigating scattering by buried steel spheres. The numerical results show that the method can be used for detecting buried objects.

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25

Cataño-Lopera, Yovanni A., Blake J. Landy, and Marcelo H. García. "Unstable flow structure around partially buried objects on a simulated river bed." Journal of Hydroinformatics 19, no. 1 (September 17, 2016): 31–46. http://dx.doi.org/10.2166/hydro.2016.060.

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The unsteady flow characteristics around two partially buried objects, a short cylinder and a truncated cone, were examined with a three-dimensional, non-hydrostatic hydrodynamic model under similar steady unidirectional currents with flow Reynolds numbers, Re, of 86,061 and 76,209, respectively. Model simulations were conducted with the two objects partially buried in a simulated rippled river bed. A Reynolds-averaged Navier–Stokes (RANS) equation model coupled with a κ-ε turbulence closure was used to validate the experimental velocity measurements. A large eddy simulation (LES) turbulence model was subsequently used to characterize the unsteady flow structure around the objects. The LES closure allowed for the characterization of highly unsteady coherent turbulent structures such as the horse-shoe vortex, the arch-shaped vortex, as well as vortex shedding in the wake of the object.

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26

Saillard, M., P. Vincent, and G. Micolau. "Reconstruction of buried objects surrounded by small inhomogeneities." Inverse Problems 16, no. 5 (October 1, 2000): 1195–208. http://dx.doi.org/10.1088/0266-5611/16/5/306.

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27

Cmielewski, O., M. Saillard, and H. Tortel. "Detection of buried objects beneath a rough surface." Waves in Random and Complex Media 16, no. 4 (November 2006): 417–31. http://dx.doi.org/10.1080/17455030600719687.

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28

Ferrara, Vincenzo, Andrea Pietrelli, Simone Chicarella, and Lara Pajewski. "GPR/GPS/IMU system as buried objects locator." Measurement 114 (January 2018): 534–41. http://dx.doi.org/10.1016/j.measurement.2017.05.014.

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29

Herman, Herman, and Sanjiv Singh. "First results in autonomous retrieval of buried objects." Automation in Construction 4, no. 2 (June 1995): 111–23. http://dx.doi.org/10.1016/0926-5805(94)00038-o.

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30

Schlicker, D., A. Washabaugh, I. Shay, and N. Goldfine. "Inductive and capacitive array imaging of buried objects." Insight - Non-Destructive Testing and Condition Monitoring 48, no. 5 (May 2006): 302–6. http://dx.doi.org/10.1784/insi.2006.48.5.302.

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31

Trucco, A., and A. Pescetto. "Acoustic detection of objects buried in the seafloor." Electronics Letters 36, no. 18 (2000): 1595. http://dx.doi.org/10.1049/el:20001065.

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32

Hill, D. A. "Electromagnetic scattering by buried objects of low contrast." IEEE Transactions on Geoscience and Remote Sensing 26, no. 2 (March 1988): 195–203. http://dx.doi.org/10.1109/36.3021.

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33

Brunzell, H. "Detection of shallowly buried objects using impulse radar." IEEE Transactions on Geoscience and Remote Sensing 37, no. 2 (March 1999): 875–86. http://dx.doi.org/10.1109/36.752207.

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34

Qu, Fenglong, Ruixue Jia, and Yanli Cui. "Inverse Conductive Medium Scattering with Unknown Buried Objects." Acta Mathematica Scientia 43, no. 5 (July 12, 2023): 2005–25. http://dx.doi.org/10.1007/s10473-023-0505-9.

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35

Simpson, C. J., M. J. Ward, D. L. Clements, S. Rawlings, and A. S. Wilson. "Buried Quasars in Radiogalaxies?" Symposium - International Astronomical Union 159 (1994): 522. http://dx.doi.org/10.1017/s0074180900176934.

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We report on the results of a near-infrared imaging survey of low-redshift radiogalaxies. We find that one of our 13 objects harbours an unresolved source at K, which we interpret as a quasar-like central engine seen through ∼ 40 magnitudes of visual extinction.

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36

Al shamy, Hussain Mumtaiz, Jafar W. Abdul Sadah, and Thamir R. Saeed. "Different techniques in detection of buried objects using ground-penetrating radar: A review." Al-Qadisiyah Journal for Engineering Sciences 14, no. 4 (May 22, 2022): 232–40. http://dx.doi.org/10.30772/qjes.v14i4.783.

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This literature reviews the work of researchers on ground-penetrating radar (GPR). This research consists of five sections starting from the first section that focuses on the general application and the advantage of the GPR system in comparison to other types of underground detection systems. The main function of the GPR system is to detect the object buried underground and at the end of the full scan, the output image represents the total signals detected by the receiver of the GPR device. One of the main applications of the GPR system is the detection of an underground object, the GPR scans the underground area and the output image represents the total of the signals detected by the receiver. The second section discusses methods for removing unwanted signals such as noise and direct waves from the output image of a GPR system. After removing the noise, the image requires further analysis to discover and interpret the buried object. The third section discusses the common methods used in the process of identifying buried objects. There are different types of buried objects and section four discusses the algorithms used to detect and identify landmines and explosive devices. Finally, the last section summarizes the paper that discussed the detection and identification process using smart algorithm technology. These types of algorithms are the most accurate, have a lower error rate and are cost-effective.

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37

Inoue, Koki, Shuichiro Ogake, Kazuma Kobayashi, Toyoaki Tomura, Satoshi Mitsui, Toshifumi Satake, and Naoki Igo. "An AR Application for the Efficient Construction of Water Pipes Buried Underground." Electronics 12, no. 12 (June 12, 2023): 2634. http://dx.doi.org/10.3390/electronics12122634.

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Unlike other civil engineering works, water pipe works require digging out before construction because the construction site is buried. The AR application is a system that displays buried objects in the ground in three dimensions when users hold a device such as a smartphone over the ground, using images from the smartphone. The system also registers new buried objects when they are updated. The target of this project is water pipes, which are the most familiar of all buried structures. The system has the following functions: “registration and display of new water pipe information” and “acquisition and display of current location coordinate information.” By applying the plane detection function to data acquired from a camera mounted on a smartphone, the system can easily register and display a water pipe model horizontally to the ground. The system does not require a reference marker because it uses GPS and the plane detection function. In the future, the system will support the visualization and registration of not only water pipes but also other underground infrastructures and will play an active role in the rapid restoration of infrastructure after a large-scale disaster through the realization of a buried-object 3D MAP platform.

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38

Bachrach, Ran, and Moshe Reshef. "3D ultra shallow seismic imaging of buried pipe using dense receiver array: Practical and theoretical considerations." GEOPHYSICS 75, no. 6 (November 2010): G45—G51. http://dx.doi.org/10.1190/1.3506560.

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Direct 3D imaging of a [Formula: see text] pipe, buried at a depth of [Formula: see text], using portable dense receiver array shows that small objects associated with large impedance contrast can be precisely imaged. Detailed velocity analysis applied to backscattered wavefield from small buried objects provides resolution of less than [Formula: see text]. Comparison of backscattered wavefield observations to analytical solutions show a generally good match. Theoretical calculations also show that the object can be detected with wavelengths much larger than its size due to the large contrast associated with its hollow shape. Dense spatial sampling is needed to capture the energy emitted from the scattering object and successfully focus it by diffraction imaging. Portable dense receiver array can provide a cost-effective solution for such tasks.

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39

Fawcett, John A. "Computing the acoustic field scattered from proud, partially buried, or totally buried cylindrical objects." Journal of the Acoustical Society of America 99, no. 4 (April 1996): 2498–500. http://dx.doi.org/10.1121/1.415657.

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40

A., Korostelev. "New Data on the Results of the Study of the Funeral and Memorial Complex the Tsagan-Khushun-II “a” on the Coast of Lake Baikal." Teoriya i praktika arkheologicheskikh issledovaniy 34, no. 1 (2022): 30–46. http://dx.doi.org/10.14258/tpai(2022)34(1).-02.

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Funeral and memorial complexes are the objects consisting of human burials and memorial structures or ritual masonry, under which there may be objects that have some symbolic meaning for the people who built them. One of such objects on the Baikal coast is the site of the Iron Age Tsagan Khushun-II in the Priolkhonye. Until now, it was considered an object with one type of funeral rite — the Elginsky, which existed on the territory of the Baikal region from the 3rd century BC to the 4th century AD. Those buried in the grave pits were laid crouched, on their sides, with their heads oriented to the southeast. However, the excavations carried out in recent years have revealed an earlier type of burial — Butukheysky. For the Butukheysky burial rite, the position of the person buried in the grave pit is elongated, on his back, with his head oriented to the southeast. Radiocarbon dates were obtained from the bones of those buried from two Butukheysky burials discovered in the southern part of the burial ground. The age of burial No. 23 corresponds to the erd — beginning of the 2nd centuries BC, the age of burial No. 31 — II — beginning of the 1st centuries BC. Thus, the Butukheysky and Elginsky burial traditions have existed together for more than two centuries. Their representatives buried their dead in the same burial grounds.

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41

Kozaczka, Eugeniusz, Grazyna Grelowska, Sławomir Kozaczka, and Wojciech Szymczak. "Detection of Objects Buried in the Sea Bottom with the Use of Parametric Echosounder." Archives of Acoustics 38, no. 1 (March 1, 2013): 99–104. http://dx.doi.org/10.2478/aoa-2013-0012.

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Abstract The paper contains results of a in situ research main task of which was to detect objects buried, partially or completely, in the sea bottom. Object detecting technologies employing acoustic wave sources based on nonlinear interaction of elastic waves require application of parametric sound sources. Detection of objects buried in the sea bottom with the use of classic hydroacoustic devices such as the sidescan sonar or multibeam echosounder proves ineffective. Wave frequencies used in such devices are generally larger than tens of kHz. This results in the fact that almost the whole acoustic energy is reflected from the bottom. On the other hand, parametric echosounders radiate waves with low frequency and narrow beam patterns which ensure high spatial resolution and allows to penetrate the sea bottom to depths of the order of tens of meters. This allows to detect objects that can be interesting, among other things, from archaeological or military point of view.

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42

Panzner, Berthold, Andreas Jöstingmeier, and Abbas Omar. "Radar Signatures of Complex Buried Objects in Ground Penetrating Radar." International Journal of Electronics and Telecommunications 57, no. 1 (March 1, 2011): 9–14. http://dx.doi.org/10.2478/v10177-011-0001-3.

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Radar Signatures of Complex Buried Objects in Ground Penetrating RadarThe evaluation of radar signatures of buried objects for three experimental ground penetrating radar setups will be addressed in this paper. The contribution will present corresponding results and experiences. The performance of the imaging capabilities of the designed radar system will be assessed by reconstruction of complex shaped test objects, which have been placed within the ground. The influence of system parameters of the ground penetrating radar have been varied systematically in order to analyze their effects on the image quality. Among the modified parameters are the step size in transverse plane, height of the antenna over ground, frequency range, frequency points, antennas and varying instrument settings. A signal processing technique based on synthetic aperture radar has been applied on the measured raw data. The focus radius around a specific target has been analyzed concerning the compromise between image quality and processing time. The experiments demonstrate that the designed ground penetrating radar systems are capable for detection of buried objects with high resolution.

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43

Billings, Dr Stephen, Dr Malcolm Cattach, and Michael Laneville. "Detection of deep buried metal objects with the UltraTEM." ASEG Extended Abstracts 2015, no. 1 (December 2015): 1–2. http://dx.doi.org/10.1071/aseg2015ab029.

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44

Tezel, N. S. "Newton's method for inverse obstacle scattering of buried objects." Journal of Integral Equations and Applications 21, no. 2 (June 2009): 317–28. http://dx.doi.org/10.1216/jie-2009-21-2-317.

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45

Erikson, Kenneth R. "Acoustical imaging interferometer for detection of buried underwater objects." Journal of the Acoustical Society of America 117, no. 5 (2005): 2683. http://dx.doi.org/10.1121/1.1932318.

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46

Dourthe, C., C. Pichot, J. Y. Dauvignac, and J. Cashman. "Microwave imaging of buried objects for ground radar tomography." Radio Science 35, no. 3 (May 2000): 757–71. http://dx.doi.org/10.1029/1998rs002128.

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47

Bertoncini, F., R. G. Kouyoumjian, G. Manara, and P. Nepa. "High-frequency scattering by objects buried in lossy media." IEEE Transactions on Antennas and Propagation 49, no. 12 (2001): 1649–56. http://dx.doi.org/10.1109/8.982443.

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Karasalo, Ilkka. "Full field modeling of multiaspect scattering from buried objects." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3946. http://dx.doi.org/10.1121/1.2936042.

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Attenborough, Keith, Qin Qin, Jonathan Jefferis, and Gary Heald. "Laboratory experiments on nonlinear acoustic detection of buried objects." Journal of the Acoustical Society of America 119, no. 5 (May 2006): 3386. http://dx.doi.org/10.1121/1.4786634.

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Gharamohammadi, Ali, Fereidoon Behnia, and Rouhollah Amiri. "Imaging Based on Correlation Function for Buried Objects Identification." IEEE Sensors Journal 18, no. 18 (September 15, 2018): 7407–13. http://dx.doi.org/10.1109/jsen.2018.2859170.

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