• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.838-848
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• 2014

We present a simulation study of an algorithm for the range and angle of arrival(AOA) estimation with an interferometric synthetic aperture radar(InSAR) altimeter using a real digital elevation model(DEM). We also illustrate a step-by-step procedure of generating raw InSAR data, as well as their range and azimuth compressed data, which is to be used for the subsequent altitude and angle estimation. The AOA is estimated using a deterministic maximum likelihood estimator(DMLE) applied to the first arrived point for each pulse in the compressed data obtained with three antennas. The range bin size and the pulse repetition interval(PRI) are much smaller than the cell size of the DEM used in this study. To make the DEM compatible to the radar parameters, we first generate a higher resolution DEM by linearly interpolating the given DEM. After a brief description of the principle of the InSAR altimeter, the algorithms for altitude and angle estimation are presented, and their performance is assessed through simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.248-253
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• 2015

In order to adapt to human's life and perform missions, a humanoid robot needs a height at least similar with children's. In this paper, we proposed a humanoid robot which is like a child who is taller than 1m. We presented showing the humanoid robot's kinematics, designing of a three-dimensional model, developing mechanisms, and the hardware structures using servo motors and compact size PC. Through this process, we designed and manufactured child humanoid robot 'CHARLES(Cognitive Humanoid Autonomous Robot with Learning and Evolutionary Systems)' that is robot is 1m 10cm tall and 8.16kg in weight. For robot's walking, we applied to ZMP-based walking technique and the creation algorithm is applied for walking patterns. Through experiments, we analyzed walking patterns according to the creation and changing parameter values.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.685-691
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• 2008

The selection of classification boundaries in fuzzy rule- based classification systems is an important and difficult problem. So various methods based on learning processes such as neural network, genetic algorithm, and so on have been proposed for it. In a previous study, we pointed out the limitation of the methods and discussed a method for fuzzy partitioning in the overlapped region on feature space in order to overcome the time-consuming when the additional parameters for tuning fuzzy membership functions are necessary. In this paper, we propose a method to determine three types of classification boundaries(i.e., non-overlapping, overlapping, and a boundary point) on the basis of statistical information of the given dataset without learning by extending the method described in the study. Finally, we show the effectiveness of the proposed method through experimental results applied to pattern classification problems using the modified IRIS and standard IRIS datasets.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.165-172
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• 2013

In this paper, high-quality mosaic image is generated by high-resolution hyperspectral strip images using scale-invariant feature transform (SIFT) algorithm, which is one of the representative image matching methods. The experiments are applied to AISA Eagle images geo-referenced by using GPS/INS information acquired when it was taken on flight. The matching points between three strips of hyperspectral images are extracted using SIFT method, and the transformation models between images are constructed from the points. Mosaic image is, then, generated using the transformation models constructed from corresponding images. Optimal band appropriate for the matching point extraction is determined by selecting representative bands of hyperspectral data and analyzing the matched results based on each band. Mosaic image generated by proposed method is visually compared with the mosaic image generated from initial geo-referenced AISA hyperspectral images. From the comparison, we could estimate geometrical accuracy of generated mosaic image and analyze the efficiency of our methodology.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.418-425
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• 1998

Stereo cameras are the most widely used sensing systems for automated machines including robots to interact with their three-dimensional(3D) working environments. The position of a target point in the 3D world coordinates can be measured by the use of stereo cameras and the camera calibration is an important preliminary step for the task. Existing camera calibration techniques can be classified into two large categories - linear and nonlinear techniques. While linear techniques are simple but somewhat inaccurate, the nonlinear ones require a modeling process to compensate for the lens distortion and a rather complicated procedure to solve the nonlinear equations. In this paper, a method employing a neural network for the calibration problem is described for tackling the problems arisen when existing techniques are applied and the results are reported. Particularly, it is shown experimentally that by utilizing the function approximation capability of multi-layer neural networks trained by the back-propagation(BP) algorithm to learn the error pattern of a linear technique, the measurement accuracy can be simply and efficiently increased.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.405-412
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• 2015

This paper represents a filter design to estimate the airspeed of a spin-stabilized, trajectory-correctible artillery ammunition. Due to the limited power and space in operational point of view, the airspeed sensor is not installed, and thus the airspeed need to be estimated using limited sensor measurements. The only IMU measurements(three-axis specific forces and angular rates) are used in this application. The extended Kalman filter algorithm is applied since a linear filter can not cover the its wide operational range in airspeed and altitude. In the implementation of the EKF, the state and measurement equations are transformed into the no-roll frame for simple form of Jacobian matrix. The simulation study is conducted to evaluate the performance of the filter under various environment conditions of sensor noise and wind turbulence. In addition, the effect of the choice in filter design parameters, i.e. process error covariance matrices is analyzed on the performance of the estimation of airspeed and angular rates.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.356-367
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• 2011

In this paper, we proposed a new car engine sealing inspection system based on image processing and understanding. The car engine sealing inspection plays very important role for protecting leakage caused by inappropriate sealing, which is a crucial point for productivity of car engines. The proposed inspection system has been aimed to enhance the previously proposed sealing inspection systems based on image processing, which have high computation complexity and low performance for correctly inspecting some contamination by oil with similar color with that of sealing. Moreover, the previously proposed system has a difficulty in installing the camera system on the sealing machine. The proposed system considers a difference of images before and after sealing obtained from one static camera. By utilizing a difference of images, the proposed system shows very robust performance using a proposed simple depth checking algorithm for some contamination cases by oil with similar color with that of sealing and the total inspection system is simple and cheap to implement. According to the experiments conducted in a real car product line, the proposed inspection system shows better inspection performance and needs smaller implementation cost than three other previously proposed system working in current car sealing inspection systems.

• Advances in Computational Design
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• v.5 no.2
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• pp.127-146
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• 2020

Building Information Modeling (BIM) is increasingly used throughout the facility's life cycle for various applications, such as design, construction, facility management, and maintenance. For existing buildings, the geometry of as-built BIM is often constructed using dense, three dimensional (3D) point clouds data obtained with laser scanners. Traditionally, as-built BIM systems do not contain the material and textural information of the buildings' elements. This paper presents a semi-automatic method for generation of material and texture rich as-built BIM. The method captures and integrates material and textural information of building elements into as-built BIM using thermal infrared sensing (TIS). The proposed method uses TIS to capture thermal images of the interior walls of an existing building. These images are then processed to extract the interior walls using a segmentation algorithm. The digital numbers in the resulted images are then transformed into radiance values that represent the emitted thermal infrared radiation. Machine learning techniques are then applied to build a correlation between the radiance values and the material type in each image. The radiance values were used to extract textural information from the images. The extracted textural and material information are then robustly integrated into the as-built BIM providing the data needed for the assessment of building conditions in general including energy efficiency, among others.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.27-32
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• 2008

Purpose : We developed a 3D CSI (chemical shift imaging) sequence that uses the PRESS (point resolved spectroscopy) excitation scheme and spiral-based readout gradients. Materials and Methods : We implemented constant-density spirals ($32{\times}32$ matrix, $24{\times}24\;cm$ FOV) which use analytic equations to enable real-time prescription on the scanner. In-vivo data from the brain were collected and reconstructed using the gridding algorithm. Results : Data illustrate that with our imaging sequence, the benefits of the PRESS technique, which include elimination of lipid artifacts, remain intact while flexible scan time versus resolution tradeoffs can be achieved using the constant-density spirals. Volumetric high resolution 3D CSI covering 5760 cm3 could be obtained in 12.5 minutes. Conclusion : Spiral-based readout gradients offer a flexible tradeoff between scan time versus resolution. By combining this feature with PRESS based excitation, efficient methods of volumetric spectroscopic imaging can be accomplished by obtaining whole brain coverage while eliminating lipid contamination.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.81-89
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• 2012

Commonly used horizontal-axis wind turbines (HAWT) have the following structure: two or three blades, a nacelle which contains power converting equipments, generators, and a tower which supports the nacelle. The generated power is transmitted from the nacelle to the ground. Due to this structure, the power transmission lines are twisted when the nacelle is yawing. Thus, slip ring or additional yaw control mechanism is required. We propose a new structure of HAWT which is free of this transmission line problem. Moreover, the size of inverter can be reduced since two generators are connected in parallel in our mechanism so that power is distributed. A controller for yawing is developed so that it works in harmony with the controller for power generation. A MPPT (Maximum Power Point tracking) algorithm is implemented for the proposed system and efficiency of the system is validated by simulation.