• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.49 no.3
• /
• pp.47-52
• /
• 2012

This paper is in regard to design and experiment about the radar's circular polarization antenna operating in the Ku band. By using the Post to manufacture the circular polarization antenna using the linear antenna, it could reduce the structural size of an antenna. 3 Posts were used in order to broaden the Axial ration Bandwidth of the circular polarization antenna. The distance and length between Posts and Post were appropriately selected for the axial ratio optimization and applied in the design. It was verified that the designed antenna has the impedence bandwidth of 12.7%, axial ratio performance less than 2dB and gain of 7.8dBi.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.9
• /
• pp.63-69
• /
• 2003

As increasing underground facilities, more effective management is needed nowadays. It is important to get an accurate information of underground facilities to manage that, so some methods of detecting location - electromagnetic induction method, ground penetration radar method, sound wave method - are used to obtain the information of underground facilities. In this study, a magnetic method to detect underground facilities was developed. In the magnetic method, underground facilities are detected by a detector and the magnetic marker which is a permanent magnet and used to marking the location by attaching underground facilities. A test field was constructed for experiment with the magnetic marker, PVC pipe, and steel pipe under ground 1.5m, and a ferromagnetic detector was used for measurement. Magnetic strengths of the magnetic marker were measured by the detector at each location in the test field, and analyzed by magnetic field analysis tool in the same condition. In the result, the underground pipes of 1.5m below were detectable within the deviation $\pm$0.2m. When For applying this method, it should be considered that ferromagnetic materials around the detector could affect a measured value.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.6
• /
• pp.314-323
• /
• 2005

This paper proposes a real-time 3D visualization system for situational awareness of Air force operations. This 3D system of situational awareness supports a high-level commander of Air force during the war game operations. These situation aware supporting data such as the aircraft track data of radar, aircraft schedule database, map and satellite image data are integrated into one structured data and those are visualized as 3D structure. By using an Out-of-Core method, we can visualize a 3D huge data in real-time in mobile notebook environment. The experiment shows several examples of 3D visualization supporting situation awareness for Air force operation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.2
• /
• pp.195-206
• /
• 2016

The remote sensing technique using SAR data have many advantages when applied to the disaster site due to its wide coverage and all-weather acquisition availability. Although a single-pol (polarimetric) SAR image cannot represent the land surface better than a quad-pol SAR image can, single-pol SAR data are worth using for disaster-induced change detection. In this paper, an automatic change detection method based on a mixture of GGDs (generalized Gaussian distribution) is proposed, and usability of the textural features and intensity is evaluated by using the proposed method. Three ALOS/PALSAR images were used in the experiments, and the study site was Norita City, which was affected by the 2011 Tohoku earthquake. The experiment results showed that the proposed automatic change detection method is practical for disaster sites where the large areas change. The intensity information is useful for detecting disaster-induced changes with a 68.3% g-mean, but the texture information is not. The autocorrelation and correlation show the interesting implication that they tend not to extract agricultural areas in the change detection map. Therefore, the final tsunami-induced change map is produced by the combination of three maps: one is derived from the intensity information and used as an initial map, and the others are derived from the textural information and used as auxiliary data.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.1
• /
• pp.130-136
• /
• 2005

A new optical digitizing system for determining the position of a cursor in three dimensions(3D) and an experimental device for its measurement are presented. A semi-passive system using light intensity modulation, a technology that is well known in radar ranging, is employed in order to overcome precision limitations imposed by background light. This system consists of a charge-coupled device camera placed before a rotating mirror and a light-emitting diode whose intensity is modulated. Using a Fresnel pattern for light modulation, it is verified that a substantial improvement of the signal to noise ratio is realized for the background noise and that a resolution of less than a single pixel can be achieved. This opens the doorway to the realization of high precision 3D digitized measurement. We further propose that a 3D position measurement with a monocular optical system can be realized by a numerical experiment if a linear-period modulated waveform is adopted as the light-modulating one.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.2
• /
• pp.189-196
• /
• 2014

Automated design program using commercial process integration and optimization program was developed for conceptual design of fighter-class aircraft. Wind tunnel test data and performance analysis results were compared for the verification of analysis tool of this program, and the usefulness of the tool was found. After integration with radar cross section analysis tool, the correlation with configuration design variables of wing, tail and performance parameters was identified by design of experiment, and the optimized configuration for weight and RCS was derived from optimization of empty weight and average frontal RCS value. After parameter definition of fuselage, the program can be implemented for full aircraft configuration.

• Journal of the Society of Disaster Information
• /
• v.14 no.4
• /
• pp.430-439
• /
• 2018

Purpose: The purpose of this study is to verify the effectiveness of maintenance method using GPR exploration by buried detective materials in the ground for efficient maintenance of recovered cavities. Method: EMI sheet, EMI paint, and ferronickel slag were used as the detection materials, and the experiment was conducted by varying the size and depth of the buried detectable material. Results: As a result of the exploration, Detectable influence range by GPR exploration was found depending on the size and depth of buried detectable material in all materials, and the possibility of using it as a detection material was confirmed.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1034-1038
• /
• 2020

In order to effectively process target recognition using radar, accurate signal information for the target is required. However, such a target signal is usually mixed with noise, and this part of the study is continuously carried out. Especially, image processing, target signal processing and target recognition for the target are examples. Since the field of target recognition is important from a military point of view, this paper carried out research on target recognition of aircraft using a tree-structured fuzzy neural networks. Fuzzy neural networks are learned by using reflected signal data for an aircraft to optimize the model, and then test data for the target are used for the optimized model to perform an experiment on target recognition. The effectiveness of the proposed method is verified by the simulation results.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.27 no.2
• /
• pp.147-155
• /
• 2024

Based on the recently developed deep learning technology, many studies have been conducted on deep learning networks that simultaneously detect and classify targets of interest in synthetic aperture radar(SAR) images. Although numerous research results have been derived mainly with the open SAR ship datasets, there is a lack of work carried out on the deep learning network aimed at detecting and classifying SAR ground targets and trained with the synthetic dataset generated from electromagnetic scattering simulations. In this respect, this paper presents the deep learning network trained with the synthetic dataset and applies it to detecting and classifying real SAR ground targets. With experiment results, this paper also analyzes the network performance according to the composition ratio between the real measured data and the synthetic data involved in network training. Finally, the summary and limitations are discussed to give information on the future research direction.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.4
• /
• pp.274-282
• /
• 2009

Various location tracking sensors; such as GPS, INS, radar, and optical equipment; are used for tracking moving targets. In order to effectively track moving targets, it is necessary to develop an effective fusion method for these heterogeneous devices. There have been studies in which the estimated values of each sensors were regarded as different models and fused together, considering the different error characteristics of the sensors for the improvement of tracking performance using heterogeneous multi-sensor. However, the rate of errors for the estimated values of other sensors has increased, in that there has been a sharp increase in sensor errors and the attempts to change the estimated sensor values for the Sensor Probability could not be applied in real time. In this study, the Sensor Probability is obtained by comparing the RMSE (Root Mean Square Error) for the difference between the updated and measured values of the Kalman filter for each sensor. The process of substituting the new combined values for the Kalman filter input values for each sensor is excluded. There are improvements in both the real-time application of estimated sensor values, and the tracking performance for the areas in which the sensor performance has rapidly decreased. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance. The trajectory of a UAV is generated in an experiment and a performance analysis is conducted with other fusion algorithms.