1,949 research outputs found
A 2D processing algorithm for detecting landmines using Ground Penetrating Radar data
Ground Penetrating Radar(GPR) is one of a number
of technologies that have been used to improve landmine
detection efficiency. The clutter environment within the first
few cm of the soil where landmines are buried, exhibits strong
reflections with highly non-stationary statistics. An antipersonnel
mine(AP) can have a diameter as low as 2cm whereas many
soils have very high attenuation frequencies above 3GHZ. The
landmine detection problem can be solved by carrying out system
level analysis of the issues involved to synthesise an image
which people can readily understand. The SIMCA (âSIMulated
Correlation Algorithmâ) is a technique that carries out correlation
between the actual GPR trace that is recorded at the field and the
ideal trace which is obtained by carrying out GPR simulation.
The SIMCA algorithm firstly calculates by forward modelling a
synthetic point spread function of the GPR by using the design
parameters of the radar and soil properties to carry out radar
simulation. This allows the derivation of the correlation kernel.
The SIMCA algorithm then filters these unwanted components
or clutter from the signal to enhance landmine detection. The
clutter removed GPR B scan is then correlated with the kernel
using the Pearson correlation coefficient. This results in a image
which emphasises the target features and allows the detection of
the target by looking at the brightest spots. Raising of the image
to an odd power >2 enhances the target/background separation.
To validate the algorithm, the length of the target in some cases
and the diameter of the target in other cases, along with the
burial depth obtained by the SIMCA system are compared with
the actual values used during the experiments for the burial depth
and those of the dimensions of the actual target. Because, due
to the security intelligence involved with landmine detection and
most authors work in collaboration with the national government
military programs, a database of landmine signatures is not
existant and the authors are also not able to publish fully their
algorithms. As a result, in this study we have compared some of
the cleaned images from other studies with the images obtained
by our method, and I am sure the reader would agree that our
algorithm produces a much clearer interpretable image
The SIMCA algorithm for processing Ground Penetrating Radar data and its use in landmine detection
The main challenge of ground penetrating radar (GPR)
based land mine detection is to have an accurate image
analysis method that is capable of reducing false alarms.
However an accurate image relies on having sufficient spatial
resolution in the received signal. But because the diameter
of an AP mine can be as low as 2cm and many soils
have very high attenuations at frequencies above 3GHz,
the accurate detection of landmines is accomplished using
advanced algorithms. Using image reconstruction and
by carrying out the system level analysis of the issues involved
with recognition of landmines allows the landmine
detection problem to be solved. The SIMCA (âSIMulated
Correlation Algorithmâ) is a novel and accurate landmine
detection tool that carries out correlation between a simulated
GPR trace and a clutter1 removed original GPR
trace. This correlation is performed using the MATLAB
R
processing environment. The authors tried using convolution
and correlation. But in this paper the correlated results
are presented because they produced better results.
Validation of the results from the algorithm was done by
an expert GPR user and 4 other general users who predict
the location of landmines. These predicted results are
compared with the ground truth data
Inverse Problem Solution in Landmines Detection Based on Active Thermography
Landmines still affect numerous territories in the whole world and pose a serious threat, mostly to civilians. Widely used non-metallic landmines are undetectable using metal detector. Therefore, there is an urging need to improve methods of detecting such objects. In the present study we introduce relatively new method of landmines' detection: active infrared thermography with microwave excitation. In this paper we present the optimization based method of solving inverse problem for microwave heating. This technique will be used in the reconstruction of detected landmines geometric and material properties
Quantum Magnetics Targets Landmine Explosives Using Quadrupole Resonance
San Diego-based Quantum Magnetics did not intend to develop the worldâs best landmine detection technology, but it just might turn out that way. For the past five years, the company has been working to develop landmine detection technology that would be so specific and effective that it would minimize false alarms, thus saving lives and limbs of U.S. soldiers, citizens and landmine sweepers alike. Although Quantum Magnetics is also developing other security-related technologies for applications such as bomb, drug and concealed-weapon detection, it has continued to keep its core objective on course, and its scientists continue to concentrate on solving the most important ingredient of landmine detectionâidentifying buried landmine explosives used in mines quickly and with few false alarms. By targeting the specific molecules of explosives (such as RDX, tetryl, PETN, and the hardest to detect, TNT), Quantum Magnetics believes its sensors alone, or in combination with other detection devices, will be instrumental in removing the estimated 60 million to 110 million landmines abandoned throughout the world
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