detection of movement and impedance changes behind surfaces using ground penetrating radar - sevket...

8/9/2019 Detection of Movement and Impedance Changes Behind Surfaces Using Ground Penetrating Radar - Sevket Demirc

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PIERS ONLINE, VOL. 7, NO. 1, 2011 35

Detection of Movement and Impedance Changes behind Surfaces

Using Ground Penetrating Radar

Sevket Demirci1, Enes Yigit2, and Caner Ozdemir1

1Department of Electrical-Electronics Engineering, Mersin University, Mersin, Turkey2Vocational School of Technical Sciences, Mersin University, Mersin, Turkey

Abstract In this paper, the utility of Ground Penetrating Radar (GPR) in electromagneticempedance change detection is demonstrated through experimental results. For this purpose, twokinds of changes; namely human movement behind walls and water leakage from embedded pipesare considered for their electromagnetic detection. In the first case, the movement behind a wall isdetected by real time monitoring of A-scan GPR data. The difference signals between two A-scanrange profiles acquired at consecutive time instants are used as an indicator of the movement.In the second case, the leakage from a plastic pipe buried in an outdoor soil environment isidentified through time series of B-scan images which are reconstructed by using a near-fieldback-projection algorithm.

1. INTRODUCTION

A common practice for the detection and localization of objects or interfaces beneath the surfaces isthe Ground Penetrating Radar (GPR) imaging. While GPR is an issue long studied in radar com-munity, there is still some implementation challenges associated with a certain specific application.These are; incorporation of optimal radar and antenna parameters for different complex mediumsand targets, accurate modeling of the propagation of the electromagnetic (EM) waves through thesubsurface, focused image formation, reliable interpretation of the data etc. Meanwhile, most ofthe GPR surveys generally concern with the imaging of stationary subsurfaces in which the ulti-mate goal is to obtain valuable information about the location and the size of the object from theresultant images. On the other hand, the potential of GPR to detect impedance changes betweentime intervals have been investigated in recent studies [13]. This can be accomplished by applying

real-time imaging processes and taking different images of the subsurface environment at differenttime instants.

Thus, to illustrate and further evaluate these capabilities and implementation challenges ofGPR, the aim of this paper is to assess whether GPR techniques can be efficiently used to detectthe movement or life signs of human being behind walls and the water leaks in buried pipes. Inthe first attempt, it was aimed to find the movement of a person behind the wall with a continuousmonitoring of A-scans. The difference signals between these consecutive range profiles weredisplayed in real time and exploited as an indication of the movement. In the second attempt,the problem of water leakage detection was considered. In our recent study [4], it was shownthat this task can be accomplished for a plastic pipe buried in an ideal case of laboratory sandpool. The research effort described herein focuses on a more realistic situation of outdoor real soilenvironment. A series of B-scan measurements were carried out and the images reconstructed by a

back-projection algorithm [5] were obtained to be able to get information about the location regionof leakage.The organization of the paper is as follows: In the following section, a brief overview of two-

dimensional (2-D) GPR data collection and processing is provided. Section 3 presents the resultsof movement detection application. In the subsequent section, B-scan imaging results for water-leakage detection problem are demonstrated. Conclusions are given in the last section.

2. BASIC GPR PRINCIPLE

In this section, a brief formulation of GPR measurement techniques is given. Fig. 1(a) shows aschematic diagram of a 2-D monostatic measurement which uses stepped-frequency continuous-wave (SFCW) radar. At each synthetic aperture point, SFCW radar transmits a waveform ofbandwidthB also called a burst which is divided into N single frequency subpulses equally spaced

across the waveform bandwidth as shown in Fig. 1(b). Each subpulse hasseconds duration andthe time interval Tbetween the pulses is set according to the desired unambiguous range.


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(a) (b)

Figure 1: 2-D monostatic GPR imaging problem. (a) Geometry. (b) Stepped-frequency waveform.

Assuming the starting carrier frequency is f0 and the fixed frequency increment is f, the

frequency of the nth pulse can be written as

fn= f0+ (n 1)f n= 1, 2, . . . , N (1)

The processing can be initiated after receiving the magnitudes and phases of the back-scatteredfield for the whole transmitted frequencies. For this static measurement also called an A-scan, thefrequency domain back-scattered field from a single point scatterer which is d distance away fromthe antenna can be written as

P(fn) = expj4

fnv

d

n= 1, 2, . . . , N (2)

where represents the reflectivity of the target and v is the velocity of the wave propagation in the

medium. For a homogeneous and lossless medium this velocity can be written as v = c/r wherec is the speed of the light in free-space and r is the relative electric permittivity of the medium.The frequency variable is related with the wavenumber, which for the two-way propagation datais defined as k = 4f/v. Hence, the back-scattered signal samples can also be represented in thespatial frequency domain as

P(kn) = exp(jknd) n= 1, 2, . . . , N (3)

Noting that the linear relationship z = v t/2 between time t and depth z can be taken underthe assumption of constant velocity v, the depth profile p(zn) of the medium can be estimatedthrough the application of one-dimensional (1-D) Inverse Fourier Transform (IFT) to the spatialfrequency data of Eq. (3). Furthermore, if 2-D images are desired, a B-scan has to be performed inwhich data are obtained by collecting a series of A-scan measurement along a synthetic aperture(see Fig. 1(a)). For each discrete point along the synthetic aperture, the back-scattered data isrecorded and thus can be represented as P(xm, fn). The focused images can then be obtained byapplying the imaging algorithms which take the near-field effects into consideration. In this study,a back-projection imaging algorithm [5] with near-field corrections is used to obtain the B-scanimages of the water leakage detection application.

3. RESULTS OF MOVEMENT DETECTION

In the first effort of our study, the goal was the experimental detection of the movement of a personbehind a wall. The considered scenario was that a person was moving behind the wall and all othersurroundings were static. For this purpose, a measurement set up for a 1-D scattering configurationwas constructed as depicted in Fig. 2(a). We have assembled a SFCW radar using Agilent E5071BENA vector network analyzer (VNA) and a rectangular horn antenna with a 30 beamwidth. The

operating bandwidth was specifically selected as 35 GHz to satisfy the proper penetration of theEM wave through the wall which has a thickness of about 30 cm. In order to keep the reflection


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(a) (b)

Computer

Network

analyzer RFamplifier

Horn antenna

Wall

Moving

person

Figure 2: Thru-wall detection of movement: (a) Schematic diagram of the experiment. (b) Radar image.

Depth

;y(m)

Synthetic aperture; x (m) Synthetic aperture; x (m) Synthetic aperture; x (m)

(a) (b) (c)

Figure 3: GPR images of water-leak experiments. (a) Image of the water-free pipe at t = 0. Image of thewater-transporting pipe (b) att = 20 min., (c) att = 30 min. after starting of water leakage. (Depth axis istaken from the antenna phase center).

from the wall surface minimal, the monostatic antenna was put very close to the wall. Then, the

transmission of continuum series of burst signals through the wall was started for desired timeduration. Then, the measured back-scattered data for each burst was recorded to a computer viaVNAs GPIB port and processed into A-scan range profiles by real-time processing. The differencesignals between consecutive range profiles were then continuously monitored. The resultant radarimage is depicted in Fig. 2(b) which clearly indicates the detection of human movement behind thewall.

4. RESULTS OF WATER LEAKAGE DETECTION

In the second effort, it was intended to test the effectiveness of GPR techniques in detecting andidentifying the water leaks from plastic pipes. For this purpose, successive B-scan experiments wereconducted in a partly homogeneous outdoor soil environment. A PVC pipe with a diameter of 5 cmwas located at a depth of 20 cm from the ground surface. Before embedding the pipe in soil, a small

hole is drilled for the leakage of water. First, a reference B-scan measurement of the water free pipewas performed. Then, after starting to injection of water into the pipe, three B-scan experimentsat regular time intervals were performed. For each scan, a synthetic aperture of length 64 cm with33 discrete spatial points and a frequency band from 0.8 to 5 GHz with 301 discrete frequencysteps were used. Two double-ridged horn antennas with a length size of 0.5 m were utilized ina bistatic configuration during the measurements. After collecting data, the B-scan images werereconstructed by using a near-field back-projection algorithm. The obtained results for various timeinstants are shown in Fig. 3. From these figures it can be interpreted that, as the water contentof the soil around the leak become larger for an evolved time, the size of the region that causesstrong EM wave reflections become also larger. Hence, EM wave could not penetrate beneath thiswater-saturated region. This phenomenon manifests itself as voids in the GPR images providingvaluable information about the location of the leak. As the time passed longer, the reflecting areabecome more and more larger and the leak position become more visible as evident in Fig. 3(c).

Hence, it can be assessed that water leakages from plastic pipes can be successfully detected byGPR techniques.


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5. CONCLUSIONS

This study demonstrated the ability of GPR to detect and localize the electromagnetic impedancechanges through surfaces. It was validated that water leakage causes a void region in the time-series of GPR images. For the movement detection problem, a simple principle of differencing theconsecutive A-scans was used to detect the movement change. Beside this simple solution, a numberof additional works has to be done on this research area. Two of them are; real-time tracking of

moving persons through walls by 2-D imaging and efficient detection of heartbeats and life signs ofpersons hidden by walls. These works will constitute the subject of our future research.

REFERENCES

1. Soldovieri, F., R. Solimene, and R. Pierri, A simple strategy to detect changes in through thewall imaging, Progress In Electromagnetics Research M, Vol. 7, 113, 2009.

2. Sachs, J., M. Aftanas, S. Crabbe, M. Drutarovsky, R. Klukas, D. Kocur, T. T. Nguyen,P. Peyerl, J. Rovnakova, and E. Zaikov, Detection and tracking of moving or trapped peoplehidden by obstacles using ultra-wideband pseudo-noise radar,Proceedings of the 5th EuropeanRadar Conference EuRAD 2008, 408411, Amsterdam, Netherlands, October 2008.

3. Eyuboglu, S., H. H. Mahdi, and H. J. Al-Shukri, Detection of water leaks using groundpenetrating radar, 3rd International Conference on Applied Geophysics Geophysics 2003,Orlando, USA, December 2003.

4. Yigit, E., S. Demirci, and C. Ozdemir, On the imaging applications of ground penetratingradar,Intern. Symp. on Electromagn. Theory URSI-2010, Berlin, Germany, August 2010.

5. Munson, D. C, J. D. OBrien, and W. K. Jenkins, A tomographic formulation of spotlight-mode synthetic aperture radar,Proc. IEEE, Vol. 71, No. 8, 917925, 1983.

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