• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.177-180
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• 2019

To improve the accuracy rate of guided weapons, many studies have been conducted on the accurate detection and identification of targets from sea clutter. Because of the variety and complicated characteristics of both sea-clutter and target signals, an active target recognition technique is required. In this study, we propose an algorithm to distinguish clutter and recognize targets by applying a fractal signature(FS) classifier, which is a fractal dimension, and a high-resolution target image(HRTI) classifier, which applies scene matching to an image formed from a scanned image. Simulation results using the algorithm revealed that the HRTI classifier recognized targets 1 and 2 at a 100 % rate, whereas the FS classifier recognized targets 1 and 2 at rates of 90 % and 93 %, respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1412-1415
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• 2012

Return signals of a ground penetrating radar(GPR) for mine detection at various frequencies and soil moisture contents are analyzed in this paper. We first compute the dielectric constant, conductivity and attenuation loss based on clay loam which is Korea standard soil. The mine-detection images of GPR at various frequencies are also obtained using the finite-difference time-domain(FDTD) technique. Then, the signal-to-clutter ratio(SCR) and received power of the radar are studied. It is shown that the variable frequency channels are suitable for a GPR to detect landmines at various soil conditions.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.746-755
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• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.756-763
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• 2013

Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.6
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• pp.758-766
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• 2017

In this paper, we propose a robust duality of CNN(Du-CNN) method which can classify the target and clutter in coastal environment for IR Imaging Sensor. In coastal environment, there are various clutter that have many similarities with real target due to diverse change of air temperature, water temperature, weather and season. Also, real target have various feature due to the same reason. Thus, the proposed Du-CNN method adopts human's multiple personality utilization and CNN technique to learn and classify target and clutter. This method has an advantage of the real time operation. Experimental results on sampled dataset of real infrared target and clutter demonstrate that the proposed method have better success rate to classify the target and clutter than general CNN method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.93-98
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• 2019

On today, optical system are the next generation weapon systems being studied in many countries, starting from USA. One of the most important technologies in optical system is a high-speed automatic target tracking system that can continuously track high-speed moving small targets. This paper designs an automatic target tracking system based on a correlated trekker that is robust against rapid shape changes for fast moving targets and small targets at a distance. The proposed system showed about 98% success rate in response to the targets that are under a complex background such as drone, ranger, etc.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.305-319
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• 2021

The overseas calibration sites such as Mongolia used for Korea Multi-purpose Satellite (KOMPSAT-5 or K5), have a disadvantage in that maintenance and repair costs are high and immediate response is difficult when an unexpected problem occurs. Accordingly, the necessity of establishing a domestic SAR calibration site was suggested, but the progress of related research is insignificant. In this paper, we investigated what conditions should be satisfied in terms of backscattering characteristics to construct a site for SAR satellite image quality evaluation and calibration. First of all, it was selected first by applying general indicators such as accessibility and availability among places recommended as satellite image calibration candidate sitesin Korea. Next, three places, site A (Goheung-gun, Jeollanam-do), site B (Jeonju-si, Jeollabuk-do), and site C (Daedeok Research Complex, Daejeon), were selected as the final candidates because they are relatively wide and easy to install AT or CR. Site A, located in Goheung-gun, Jeollanam-do, was best considered in terms of slope measurements, minimum site area to obtain ISLR, uniformity of DN values and backscatter coefficients, interference by strong reflectors, and backscatter clutter level.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.431-437
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• 2018

We analyzed the feasibility of detecting wave gliders moving on the sea surface using SAR images. For the experiment, a model was constructed and placed on the sea using a towing ship before and after the satellite observation time. In the acquisition of KOMPSAT-5 image, high resolution SAR data of spotlight mode was collected considering the small size of wave glider. As a result of the backscattering intensity analysis around the towing ship along with wave glider, several scattering points away from the ship were observed, which are not strong but clearly distinguished from the surrounding clutter values. Considering the distance from the center of the ship, it seems to be a signal by the wave glider. On the other hand, it is confirmed that the wave glider can be detected even at the very low false alarm rate ($10^{-6}$) of the target detection using CFAR. Although the scatter signal by the wave glider could be distinguished from the surrounding ocean clutter in the high resolution SAR image, further research is needed to determine if actual wave gliders are detected in various marine environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.141-149
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• 2007

Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.

• 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.