• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.201-208
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• 2014

The performance of a landmine detection system depends on consistent extractions of the features of landmines. Since landmines have diverse sizes, it is critical to select an appropriate window size to represent the landmine region consistently. Conventional detection systems are incapable of extracting consistent landmine features because they employ fixed window sizes. This paper proposes a window size selection method according to the size of a landmine. The proposed method selects an appropriate window size based on the type of a landmine estimated from the response signal of the system. Data on various types of soils and landmines were generated from a simulation program to evaluate the performance of the proposed method. The results verified that the proposed method, which employs an adaptive window size, yields a better landmine detection rate than the conventional methods, which employ fixed window sizes.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.74-84
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• 2017

Since a soldier manages a hand-held landmine detector by hands, it is necessary to develop a system that can detect the target quickly and accurately. However, the hand-held landmine detector used in Korea has a problem that it can only detect the metal mines. Therefore, it is important to solve the problem and to develop a hand-held landmine detection system suitable for the Korean environment. In this paper, we propose a hand-held landmine detection system suitable for the Korean environment using ground penetrating radar. The proposed system uses depth compensation, matched filtering, and frequency shifting filtering for preprocessing. Then, in the detection step, the system detects the target using the edge ratio. In order to evaluate the proposed system, we buried landmines in sandy loam which is most of the soil in Korea and obtained a set of ground penetrating radar data by using a hand-held landmine detector. By using the obtained data, we carried out some experiments on the size and position of the patch and the shifting frequency to find the optimal parameter values and measured the detection performance using the optimized values. Experimental results show that the proposed preprocessing algorithms are suitable for detecting all landmines at low false alarm rate and the performance of the proposed system is superior to that of previous works.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.3-12
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• 2016

This paper describes the development of the ground penetrating radar (GPR) system using UWB impulse radar with 48 Channel array. GPR is an effective alternative technology to resolve th disadvantages of metal detectors. Metal detectors have a very low detection probability of non-metallic landmine and high false alarm rates caused by metallic materials under the ground. In this paper, we use the mono-cycle pulse waveform with about 600 ps pulse width to obtain high resolution landmine microwave images. In order to analyze performances of this system, we utilize indoor test facility that made up of rough sandy loam which representative Korean soil. The mimic landmine models of metal/non-metal and anti-tank/anti-personnel landmines buried in DMZ (demilitarized zone) of Korea are used to analyze the detection depth and the shape of the mines using microwave image.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.270-279
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• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.509-516
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• 2011

In this paper, a ground penetrating radar(GPR) system is implemented for landmine detection. The performance of the GPR system is associated with the characteristics of local soil and buried target. The choice of the center frequency and the bandwidth of the GPR system are the key factors in the GPR system design. To detect a small and shallow target, the higher frequencies are needed for high depth resolution. We have been designed, fabricated and tested a new impulse generator using step recovery diodes. The measured impulse response has an amplitude of 6.2V and a pulse width of 250ps. The implemented GPR system has been tested real environmental conditions and has proved its ability to detect a small buried target.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.217-231
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• 2015

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.