• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.13-22
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• 1989

Underwater channels can be regarded as time-varying systems in view of the acoustical characteristics due to the fact that the characteristics of the channel are affected by the environmental and geometrical conditions. Especially in shallow water case, the surface and bottom conduct as a waveguide so echo effect due tu the multipath reflections are severe. Therefore in shallow water communications, it is very important to equalize the transmitted signals distorted by the underwater channels with time-varying multipath fading. In this paper an equalizer system which employs the frequency domain adaptive filter to equalize the channels using inverse modeling technique is introduced.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.248-255
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels. however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results are clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the firstpart are used to prepare a set of data for learning process. Tunnel behavior especially the displacements of the lining has been exclusively investigated for the back analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.103-107
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• 2013

In this paper, A real-time lane tracking algorithm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Lane feature that correspond to area of interest and RANSAC are used to detect lane candidates. And driving lane is decided by clustering of lane candidates. Finally, detected lane is tracked using the Kalman filter. Experimental results show that the proposed algorithm can be processed within 30ms and its detection rate is approximately 90% on the highway in a variety of environments such as day and night.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.277-284
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• 2014

The detection method of curves for the lanes which is powerful for the variation by utilizing the lane variation vector and cardinal spline on the inverse perspective transformation screen images which do not required the camera parameters are suggested in this paper. This method detects the lane area by setting the expected lane area in the s frame and next s+1 frame where the inverse perspective transformation and entire process of the lane filter are adapted, and expects the points of lane location in the next frames with the lane variation vector calculation from the detected lane areas. The scan area is set from the nextly expected lane position and new lane positions are detected within these areas, and the lane variation vectors are renewed with the detected lane position and the lanes are detected with application of cardinal spline for the control points inside the lane areas. The suggested method is a powerful method for curved lane detection, but it was adopted to the linear lanes too. It showed an excellent lane detection speed of about 20ms in processing a frame.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.213-218
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• 2021

It is known that total least-squares method shows better estimation performance than least-squares method when noise is present at the input and output at the same time. When total least squares method is applied to data with time series characteristics, Recursive Total Least Squares (RTS) algorithm has been proposed to improve the real-time performance. However, RTLS has numerical instability in calculating the inverse matrix. In this paper, we propose an algorithm for reducing numerical instability as well as having similar convergence to RTLS. For this algorithm, we propose a new RTLS using Iterative Wiener Filter (IWF). Through the simulation, it is shown that the convergence of the proposed algorithm is similar to that of the RTLS, and the numerical robustness is superior to the RTLS.

• Journal of Ocean Engineering and Technology
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• v.28 no.1
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• pp.55-63
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• 2014

In this paper, we propose an threshold-based Schur algorithm for estimating the media characteristics of sub-bottom multi-layers by using the signal generated by a parametric array transducer. We use the KZK model to generate a parametric array signal, and use the proposed threshold-based Schur algorithm for estimating the reflection coefficients of multiple sea bottom layers. Using computer simulation, we verify that the difference frequency component generated by the KZK model prevails over the signals of primary frequencies at long range. For the simulation, we use the transmit signal generated by the KZK and the reflected signal obtained from a lattice filter model for the seawater and sub-bottom of multi-level non-homogeneous layers. Through the simulation, we verify that the proposed threshold-based Schur algorithm can give much more accurate and efficient estimates of the reflection coefficients than methods using received signal, matched filter output signal, and normal Schur algorithm output.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.18-27
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• 2020

In order to estimate the launch point of a high-speed vehicle, predicting the various characteristics of the vehicle's movement, such as drag and thrust, must be preceded by the estimation. To predict the various parameters regarding the vehicle's characteristics, we build the IMM filter specialized in predicting the parameters of the post-launch phase based on flight dynamics. Then we estimate the launch point of the high-speed vehicle using Inverse Dynamics. In addition, we assume the arbitrary error level of the radar for accuracy of the prediction. We organize multiple-dimensioned IMM structures, and figure out the optimal value of parameters by comparing the various IMM structures. After deriving the optimal value of parameters, we verify the launch point estimation error under certain error level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.645-650
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• 2015

Image restoration is required when the image is blurred due to out of focus or motion during the image acquisition. This type of image restoration is known as ill-posed inverse problem because the estimate of an original image should be derived from only one blurred image. This paper introduces a reference image to facilitate the restoration process. The experimental result shows that computation time is significantly reduced, compared with other methods. The proposed method obtains the estimate of the kernel used in blurring processing. New cost function is defined to update both the image and the kernel alternately. In the last stage, Wiener filter produces the estimate of an original image using the kernel and the reference image.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.460-470
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• 2011

This paper presents a dynamic workspace control method of underwater manipulator considering a floating ROV (Remotely Operated vehicle) motion caused by sea wave. This method is necessary for the underwater work required linear motion control of a manipulator's end-effector mounted on a floating ROV in undersea. In the proposed method, the motion of ROV is modeled as nonlinear first-order differential equation excluded dynamic elements. For online manipulator control achievement, we develop the position tracking method based on sensor data and EKF (Extended Kalman Filter) and the input velocity compensation method. The dynamic workspace control method is established by applying these methods to differential inverse kinematics solution. For verification of the proposed method, experimental data based test of ROV position tracking and simulation of the proposed control method are performed, which is based on the specification of the KORDI deep-sea ROV Hemire.

• Journal of Power Electronics
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• v.15 no.4
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• pp.899-909
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• 2015

A dual-input boost-buck converter with coupled inductors (DIBBC-CI) is proposed as a thermoelectric generator (TEG) power conditioner with a wide input voltage range. The DIBBC-CI is built by cascading two boost cells and a buck cell with shared inverse coupled filter inductors. Low current ripple on both sides of the TEG and the battery are achieved. Reduced size and power losses of the filter inductors are benefited from the DC magnetic flux cancellation in the inductor core, leading to high efficiency and high power density. The operational principle, impact of coupled inductors, and design considerations for the proposed converter are analyzed in detail. Distributed maximum power point tracking, battery charging, and output control are implemented using a competitive logic to ensure seamless switching among operational modes. Both the simulation and experimental results verify the feasibility of the proposed topology and control.