• 한국지구물리탐사학회:학술대회논문집
• /
• 2006.06a
• /
• pp.9-14
• /
• 2006

Estimations of depth, magnetic orientation, and strength of dipole moments aid discrimination between unexploded ordnance (UXO) and non-UXO using magnetic surveys. Such estimations may be hindered by geologic noise, magnetic clutter, and overlapping tails of nearby dipole fields. An improved method of inversion for anomalies of single or multiple dipoles with arbitrary polarization was developed to include intra-inversion filtering and estimation of background field gradients. Data interpolated to grids are flagged so that only nodes nearest to measurement stations are used. To apply intra-inversion filtering to such data requires a gapped filter. Moreover, for data with significant gaps in coverage, or along the edges or corners of survey areas, intra-inversion filters must be appropriately modified. To that end, edge-adaptive and gapped gradient-nulling filters have been designed and tested. Applications are shown for magnetic field data from Chongcho Lake, Sokcho, Korea and the U. S. Army's Aberdeen Proving Ground in Maryland.

• Journal of Radiation Industry
• /
• v.9 no.3
• /
• pp.137-141
• /
• 2015

A single-shot dual-energy x-ray imaging technique has been developed using a sandwich detector by stacking two detectors, in which the front and rear detectors respectively produce relatively lower and higher x-ray energy images. Each detector layer is composed of a phosphor screen coupled with a photodiode array. The front detector layer employs a thinner phosphor screen, whereas the rear detector layer employs a thicker phosphor screen considering the quantum efficiency for x-ray photons with higher energies. We have applied the proposed method into the inspection of printed circuit boards, and obtained dual-energy images with background clutter suppressed. In addition, the single-shot dual-energy method provides sharper-edge images than the conventional radiography because of the unsharp masking effect resulting from the use of different thickness phosphors between the two detector layers. It is promising to use the single-shot dual-energy x-ray imaging for high-resolution nondestructive testing. For the reliable use of the developed method, however, more quantitative analysis is further required in comparisons with the conventional method for various types of printed circuit boards.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.11
• /
• pp.898-905
• /
• 2018

In this work, infrared targets for a developed hardware-in-the-loop simulation(HILS) system are proposed for a performance test of a dual-sensor imaging seeker equipped with an infrared and a visible sensor that can lock and track for ground and air targets. This integrated system is composed of 100 modules of heat and light sources to simulate various kinds of target and the trajectory of moving targets based on scenarios. It is possible to simulate not only the position, velocity, and direction for these targets but also background clutter and jamming environments. The design and measurement results of an infrared target, such as the HILS system configuration, developed for testing and evaluation of a dual-sensor imaging seeker are described. In the future, it is planned to test the lock-on and tracking performance of an imaging seeker equipped with single or dual sensors dynamically in real time based on a simulation flight scenario in the developed HILS system.

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

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.6
• /
• pp.103-114
• /
• 2019

Moving-target detection using frequency-modulated continuous-wave (FMCW) radar systems has recently attracted attention. Detection tasks are more challenging with noise resulting from signals reflected from strong static objects or small moving objects(clutter) within radar range. Robust Principal Component Analysis (RPCA) approach for FMCW radar to detect moving objects in noisy environments is employed in this paper. In detail, compensation and calibration are first applied to raw input signals. Then, RPCA via Gradient Descents (RPCA-GD) is adopted to model the low-rank noisy background. A novel update algorithm for RPCA is proposed to reduce the computation cost. Finally, moving-targets are localized using an Automatic Multiscale-based Peak Detection (AMPD) method. All processing steps are based on a sliding window approach. The proposed scheme shows impressive results in both processing time and accuracy in comparison to other RPCA-based approaches on various experimental scenarios.

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