1. 1
Capabilities and limitations of
Ground Penetrating Radar
Joshua Dee Smith, Brigham Young University, Electrical and Computer Engineering
Index Terms—Ground Penetrating Radar, Land Mine Detec-
tion
Abstract—One hundred and ten million land minds have
been distributed throughout the world across more than seventy
different countries, and ninety percent of the victims of these
devices are civilians. Plastic land mines are very prevalent and
tend to attract younger victims with their bright colors [1].
To help remove these hazards an imaging method that can
identify plastic and metal mines without making contact with the
ground is necessary. A Ground Penetrating Radar (GPR) system
is capable of identifying metal and plastic mines by launching
microwave radio frequencies into the ground to detect changes in
permittivity. Understanding these changes in permittivity allows
us to identify potentially dangerous objects hidden just below the
surface [2]–[8].
I. INTRODUCTION
According to the United Nations and their international
researchers, fifteen to twenty thousand individuals are maimed
or die from exploding land mines each year. Of those injured,
the majority are children similar to the boy shown in figure 1.
The current cost to remove a land mine is anywhere from three
hundred dollars to one thousand dollars per mine, and for every
five thousand land mines successfully cleared, one worker will
die and two others will be severely injured. To make matters
worse, land mines can remain active for decades. Some land
mines set during World War II are still active today [1].
Fig. 1. This figure shows a civilian victim of a land mine. This image was
provided by Handicap International.
Land mines and improvised explosives are a weapon of
choice by terrorists around the world today. Every day more
explosives are being placed in roadways, walking paths, and
around important infrastructure to impede movement and in-
crease fear. These explosives put our soldiers and the civilians
they protect in danger each day. These new explosive devices
use materials such as plastic and ceramics that cannot be
detected with metal detectors, but can still do significant
damage as shown in figure 2. These new materials, removal
hazards, and the shear size of the problem have encouraged
researchers and private companies to develop methods which
safely and accurately detect mines hidden in an area. Ground
Penetrating Radar (GPR) systems provide a non-destructive
method that can be safely deployed to quickly and accurately
determine the locations of mines hidden below the ground.
Fig. 2. This figure shows US tanks destroyed by land mines and other
improvised explosives durring the Gulf War. This image was provided by
http://www.group73historians.com/ .
GPR systems provide a safe method for locating land
mines with precision. The system described in this paper was
developed by NIITEK and uses a synthetic aperture radar
antenna that is suspended above the ground in front of an
armored vehicle similar to the one shown in figure 3. With a
suspended antenna, the truck will not accidentally detonate a
mine and endanger the operator. The GPR system can detect
a mine made of metal or plastic in three dimensions which
gives the disposal team the best chances of safely removing or
disposing of the mine. The system can also paint the location
of a mine as well as tag the location of the mine using
corrected GPR. To improve safety in extremely dangerous
areas, a smaller version of the GPS system can be attached to
drones and the be operated from a safe distance as shown in
figure 4. The need to safely remove these mines is growing
and developments in GPR are rising to meet this need.

2. 2
Fig. 3. This figure shows the NIITEK GPR system mounted on the front of
a tractor. This image was provided by NIITEK at www.niitek.com.
Fig. 4. This figure shows a drone that has been fitted with a smaller version
of the GPR system. This image was provided by NIITEK at www.niitek.com.
II. BASIC DESIGN AND IMPLEMENTATION OF GPR
The theory behind GPR is similar to that of other radar
systems. A simple model consists of a two antenna system,
one dedicated to transmission and the other to reception of the
return signal. Coupled with the receive antenna is an analog
to digital converter and a form of digital signal processing
to improve the received data. The digitally adjusted return
signal data and detected mine information are then given to
the operator through a digital display. A block diagram of the
process is shown in figure 5.
This particular system has been developed by a private
corporation with assistance from the American government.
A sample set of data has been recored by the military on
a specially designed dummy mine field using this system,
and many research groups are using this data to develop
algorithms for detecting mines with greater probabilities and
lower constant false alarm rates. The specific SNR for varying
ground types is not given directly in the literature, but Zhu
and Wilson describe the system as having extremely low self-
noise, low coupling, and an extremely high signal to noise
ratio (SNR) [9], [10]. Information on the system specifications
Fig. 5. This figure shows a block diagram for a basic GPR system.
is limited but an explanation is given of how test data is
acquired. The antenna array is 1.2 meters wide and contains 24
individual v-dipole antennas spaced 5 centimeters apart. This
creates twenty four individual channels that sample 416 range
points below the surface for every 5 centimeters of lateral
movement. A sample is taken roughly every 8 picoseconds.
The bandwidth of this system can range from 200MHz to
7GHz and this is adjusted to help account for varying ground
conditions [9], [10]. This sampling provides the user with a
three dimensional block of data from which signal processing
can be used to detect mines and other explosive devices. An
example of how the system is arranged is shown in figure 6,
and an example of the system return for a land mine is shown
in figure 7.
Fig. 6. This figure shows how the NIITEK array gathers data as it moves
through a mine field.
If I were to design a similar system I would begin by
evaluating the targets. Lets suppose anti-personal land mine
is about 5 centimeters in diameter on average, and an anti-
tank mine is roughly 10 centimeters in diameter on average
according to UN statics. If we apply the general equation for
determining the radar cross section (RCS) of a spherical target,
σ = π ∗ r2
, (1)

3. 3
Fig. 7. This figure shows the GPR return for a metal land mine [9].
then we can calculate a simple approximation for the RCS of
a generic anti-personal land mine and an anti-tank land mine.
This would be a very rough approximation and a better method
would need to include the permittivity and permeability of
the materials in question. These properties are often what
create the strongest effects with GPR return signals. Once we
have established the size of our smallest target we could use
this information to determine an appropate wave length. After
choosing an appropriate wave length, the necessary frequency
could then be calculated as,
f =
c
λ
. (2)
The Niitek system uses a series of 24 v-dipole antennas in their
array. We might assume the effective area of the antenna is
determined using the figure 8 assuming the v-dipole antenna
is using two quarter wave length sections to create a single
half wave length antenna. From this assumption the antenna
gain could be found using,
G =
4πAe
λ2
. (3)
It would be impractical to bury mines too deep, this forces
most to be buried close to the surface. If the average mine is
buried with in 25 centimeters of the surface, then we should set
a maximum range to be at least half a meter to ensure detection
of even overly deep land mines. We know that the system
will receive data from 416 range bins per antenna for every 5
centimeters of lateral movement. The individual measurements
are taken in about 8 picoseconds. A pulse width of 0.25
nanoseconds could be sufficient to transmit an excitation signal
under proper conditions, and this pulse width is used to define
the system’s bandwidth using,
B =
1.2
τ
. (4)
Fig. 8. This shows a v-dipole and the method I used to estimate its effective
area.
We will assume the system losses are small based on reports
given by the manufacturer, the department of defense, and
other researchers who have access to field data. According
Daniels [11], [12], a GPR systems main factor in determining
the range of the system is the path loss. When sending an
electromagnetic signal into the ground, the losses will be so
large, in comparison to air, that the effects will be in the near
field instead of the far field. The target of interest will be
within centimeters instead of kilometers. The total path loss
for a given range is given in equation 5. [13], [14]
LT = Le + Lm + Lt1 + Lt2 + Ls + La + Lsc, (5)
where LT is the total path losses, Le is the loss in the
antenna efficiency, Lm is the antenna mismatch losses, Lt1
is the transmission losses from air to the material, and Lt2 is
the retransmission losses. In this equation Ls is the antenna
spreading loss, La is the attenuation loss, and Lsc is the target
scattering loss. The maximum range a GPR can achieve is
directly related to the systems operating frequency and the
losses related to the propagation path of the radar. A simple
example of a GPR system showing its range, footprint, and
spreading is shown in figure 9.
Antenna losses, Le, and antenna mismatch losses, Lm, are
directly related to the antenna used in the system and the way
it is connected to the transmitter and receiver. These losses
are often small and can be controlled with proper design and
construction.
Transmission losses, Lt1, and retransmission losses, Lt2, are
losses related to the coupling of the radar system to the ground.
Common GPR systems would be lying flat on the ground
and this would allow the antenna to couple directly with the
ground minimizing negative effects caused at the surface. In
land mine detection it is important to maintain an air gap
between the antenna and the ground. In figures 3 and figure 4
we see that the radar antenna is lifted off the ground to reduce
the chance of unintentional detonation of land mines. This gap
requirement forces this GPR system to couple the antenna to
the ground through the air. Indirect coupling adds an additional
loss media while introducing reflections and fringing from the
interaction with the surface of the ground. These additional
losses can be mitigated using proper signal processing.

4. 4
Fig. 9. This figure shows a simple example of a standard GPR coupled
directly to the ground.
The spreading loss, Ls, is the loss related to the ratio of the
power received versus the power transmitted. A GPR system
assumes that the beam travels directly below the transmitting
antenna in a form more like a pencil beam, but in actuality
the beam will spread as it interacts with the soil, clutter, and
targets. This spreading causes the return signal to be weaker
than expected. The loss associated with this weakening in
described as
Pr
Pt
=
GtGrσ
(4πR2)
2 . (6)
In this equation Gt is the gain of the transmitting antenna, GR
is the gain of the receiver, σ is the radar cross section of our
target, and R is the range to our target. Using this equation we
can define our spreading loss as the ratio of power received
versus power input, and if we were detecting point charges
then R would be raised to the fourth power. This equation
changes slightly for different shaped targets [11], [12].
Target scattering losses, Lsc are dependent upon the geom-
etry of the target, its material composition, and its location.
Traditional land mines were made of metal and thus provide
an excellent return signal for our radar system if located above
a threshold depth. Our ability to detect plastic land mines and
other explosive devices depends heavily upon the dielectric
properties of the materials in which they were buried. A sharp
contrast in relative permittivity will give a stronger return than
a very weak or gradual change in permittivity.
Material attenuation losses, La describe the losses associ-
ated with traveling through the different layers of materials
under the ground. Different soil types have different loss
parameters which are directly related to the material’s relative
permittivity, permeability, and loss tangent. This parameter is
also affected by the users choice in operating frequency, high
frequencies give better resolution at reduced ranges and low
frequencies give reduced resolution at greater ranges. Daniels
gives a useful table of common soil elements and their losses
at a reference frequency [11], [12].
Approximations for these losses were chosen based on
Parameter Decibel Value
RCS for Anti-T* -54.1416 dB
RCS for Anti-P* -66.1784 dB
Wavelength -26.0206 dB
Frequency 135 dB
Antenna Gain 55.9868 dB
Maximum Range -6.0206 dB
System Temperature 49.5424 dB
Pulse width -192.041 dB
Bandwidth 193.625 dB
System Losses 3 dB
Antenna Efficiency -4 dB
Antenna Mismatch -1 dB
Losses Antenna to Ground -2 dB
Losses Ground to Antenna -2 dB
Spreading Losses -20 dB
Target Attenuation loss 1 dB
Target Scattering Anti-T* -54.1416 dB
Target Scattering Anti-P* -66.1784 dB
Transmit Power 0 dB - 98.068 dB
TABLE I
SYSTEM PARAMETERS THAT I WOULD USE TO FIND LAND MINES WITH
THE NIITEK SYSTEM. *ANTI-P STANDS FOR ANTI-PERSONAL AND
ANTI-T SANDS FOR ANTI-TANK
example situations given by Daniels [11] for use my system.
To determine the depth to a detected target, the velocity
of propagation, travel time, and the relative permittivity of
the surrounding material is needed. Electromagnetic waves
propagate at the speed of light in a vacuum, but when they
pass through material with electric properties, these waves will
travel with a relative speed given as
νr =
c
√
r
. (7)
Using this relative velocity, νr, and the time delay between
transmission and reception, we can calculate the depth of the
identified target.
d = νr
t
2
(8)
A table of my system specifications based on the system
in question is shown in table II.
These are system parameters that could fall within the range
of those used on the NIITEK system and these values predict
SNR values between 150 dB to over 250 dB. The SNR values
were calculated using
SNR =
PtG2
λ2
σ
(4π)
3
R4kT0FBL
, (9)
where Pt is the transmit power, G is the antenna gain, λ is the
wavelength, σ is the appropate RCS, R is the desired range,
k is the Boltzmann constant, T0 temperature related noise, F
is the system noise, B is the bandwidth, and L is the total
propagation losses. These large SNR values are undoubtedly
over predicted, but they show that the system is capable of
producing SNR values large enough to be useful in advanced

5. 5
signal processing. This particular treatment would be good for
a situation where the soil is relatively dry and homogeneously
mix throughout our maximum range. If instead we were eval-
uating an area with rocks, buried debris, and additional clutter;
an entirely different system configuration would be necessary.
This is why the NIITEK system has certain parameters such
as the pulse width or transmit power that can be configured
in the field.
III. RADAR RETURN
The GPR system assumes the return measured by the
antenna is caused by reflections coming from directly below
the system. Figure 9 show that the signal spreads from the
transmitter in a cone shape. This pattern allows the radar to see
a target without being directly over the device, but it adds an
artifact in the return image. When the system detects a target
that is at an angle with the detector, as seen with position 1
in figure 10 for example, the system assumes that the target
is directly below the transmitter, but at a deeper value. As the
system moves over the target, the prediction of an actual depth
improves until our antenna is found directly over the target.
Once directly over the target an accurate depth value can be
computed. An example of this process and its resulting signal
response are shown in figure 10, and a real image with this
same artifact is shown in figure 11.
Fig. 10. This figure shows an example of a standard GPR as it is moved
across a target of interest. The hyperbolic pattern is caused by the false depth
prediction associated with a travel time and velocity of travel.
The data extracted from measuring and processing the return
signal is used to generate two and three dimensional images
of targets contained in the soil structure. Unfortunately these
images are not easily evaluated and the level of expertise
necessary to interpolate the data increases as the signal to
noise ratio (SNR) decreases. Increasing the SNR available
in the GPR signal will result in a higher detection rate and
thus increase the longevity of the system and its users, and to
improve SNR the operator can adjust the bandwidth to match
current ground conditions. Another approach to improving
detection involves the use of algorithms to identify targets
in the data. Algorithms such as feature extraction developed
by Quan Zha [9], [10] would simplify the evaluation of data
and can be used to automate the entire process. Automated
detection allows GPR equipped drones to work in a more
Fig. 11. In this figure: a) is an example of the return from a metal mine,
and b) is the return from a plastic mine. Notice in these images that the mine
is centered under the arc of the hyperbolic pattern created as the GPR was
moved across the signal. [10]
autonomous capacity, and would allow civilians trained in
mine disposal this additional tool without much additional
training. The high signal to noise ratio achieved in the Niitek
system provides an opportunity to develop innovative methods
for automated detection of land mines.
IV. DEVELOPMENT OF ALGORITHMS TO IMPROVE
DETECTION
Thanks to the systems high SNR, a number of different
algorithms have been developed in recent years to improve
a systems ability to accurately identify both metal and non-
metal land mines in real time [9], [10]. One method marks the
highest return amplitude measurement of the 416 range bins
that is found closest to the surface from each of the twenty
four antennas. As the system moves forward it compares the
high return points in three dimensions using a polynomial fit
to look for hyperbola shapes. If the high return points form
a hyperbola in two different directions centered at a range
point, then the system has detected a mine. Figure 12 gives
an example of this process in 2 dimensions.
V. CONCLUSION
The presence of land mines and improvised explosive de-
vices on the battle field endangers our soldiers and this would
be reason enough to peruse this technology, but unlike soldiers,
land mines do not go home and they can not differentiate
between civilian and solider. These lethal devices need to be
safely and efficiently removed from current battlefields as well
as those of old. Continuing improvements to GPR specifically
designed to find these devices will help to achieve this goal.

6. 6
Fig. 12. This is an example of how polynomial fitting could be used to find
a land mine. The highest high return points are marked per antenna. These
points are then compared using a polynomial fit algorithm. If they form a
hyperbola then a mine is detected.
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