• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.173-180
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• 2006

An airborne radar is an essential aviation electronic system of the aircraft to perform various missions in all weather environments. This paper presents the design, development, and test results of the multi-mode pulsed Doppler radar system test model for helicopter-borne flight test. This radar system consists of 4 LRU units, which include ANTU(Antenna Unit), TRU(Tx Rx Unit), RSDU(Radar Signal & Data Processing Unit) and DISU(Display Unit). The developed technologies include the TACCAR processor, planar array antenna, TWTA transmitter, coherent I/Q detector, digital pulse compression, DSP based Doppler FFT filtering, adaptive CFAR, IMU, and tracking capability. The design performance of the developed radar system is verified through various helicopter-borne field tests including MTD (Moving Target Detector) capability for the Doppler compensation due to the moving platform motion.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.2
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• pp.218-225
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• 2015

Inverse synthetic aperture radar(ISAR) is coherent imaging system formed by conducting signal processing of received data which consists of radar cross section(RCS) reflected from maneuvering target. A novel algorithm is proposed to compensate inter-pulse motion(IPM) for the purpose of forming an well-focused ISAR image through signals generated by stepped chirp waveform( SCW). The velocity and acceleration of the target related to IPM are estimated based on particle swarm optimization (PSO) which has been widely used in optimization technique. Furthermore, a modified PSO which enables us to improve the performance of PSO is used to compensate IPM in a very short-time. Simulation results using point scatterer model of a Boeing-737 aircraft validate the performance of the proposed algorithm.

• The Journal of Information Systems
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• v.27 no.3
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• pp.1-24
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• 2018

Purpose The purpose of this study is to attempt to incorporate power theory to evaluate information capability of SCM adopters. Therefore, this study focuses on the relationship of information sharing, partnership quality, and information capacity according to the power intensity of the variables of SCM. and CSV value creation. Design/methodology/approach The questionnaire of SCM builder was conducted and 302 samples were analyzed. Based on the theoretical background of power and information capacity, we set up a structural equation model. Hypothesis testing and statistical analysis were done through AMOS and SPSS. Findings First, it shows that the compensation power among the constrained power has a positive effect on the partnership quality, and the legitimacy power has the positive influence only on the information sharing. Compulsive power, compensation, and legitimacy, which are generally restrictive powers, may reduce the quality of information sharing and partnership, but the results of this study are rather higher. Second, both non-binding power expertise and criterion have a positive effect on information sharing and partnership quality. Third, information sharing has a positive effect on partnership quality. Supporting a number of research results, it is well reflected in SCM attributes where interdependence is important. Fourth, information sharing and partnership quality have a positive effect on information capacity. Information literacy has become an essential element in modern management. Fifth, the enhancement of CSV value creation plays a role of a controlling variable to further strengthen information sharing through non - binding power attribute, expertise and conformity. In addition, the strengthening of CSV value creation has been shown to play a role as a controlling variable to further strengthen the quality of partnership through the non-binding power attribution, but expertise has been rejected.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.46-56
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• 1999

A predictive controller is designed based upon stochastic methods for compensation time-delay effect on a system which has inherent time-delay caused by the spatial separation between controllers and actuators. The predictive controller estimates current outputs through linear prediction methods and probability functions utilizing previous outputs, and minimizes the malicious phenomena caused by the time-delay in precision control systems. To demonstrate effectiveness of this control methodology, we applied this algorithm for the control of a tele-operated DC servomotor. The experimental results show that this predictive controller is superior to the PID controller in terms of convergence-characteristics, and show that this controller expands the maximum allowable time-delay for a system maintaining the stability. Since the proposed predictor does not require models of plants - it requires only stochastic information for outputs --, it is a general scheme which can be applied for the control of systems which are difficult to model or the compensator of PID control.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1531-1538
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• 2015

In this paper, we proposed receiver structure based on an iterative turbo equalization to cope with phase difference between two sensors in MIMO underwater communication channel. In a space-time coded system, it is often assumed that there are no phase errors among the multiple transmitter and receiver chains. In this paper, we have studied the effect of the phase errors between different transmit sensors and different propagation paths in the environment of MIMO underwater communication system, and have shown through BER performance by computer simulations that the bit-error-rate performance can be severely degraded. A decision-directed estimation and compensation algorithm has been proposed to minimize their effects on the system performance. In this paper, we investigate the phase differences and their effects on multiple-input and multiple-output systems, and propose a compensation algorithm for underwater channel model to minimize their effects.

• Earthquakes and Structures
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• v.12 no.4
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• pp.425-436
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• 2017

Vibration control using a tuned mass damper (TMD) is an effective technique that has been verified using analytical methods and experiments. It has been applied in mechanical, automotive, and structural applications. However, the damping of a TMD cannot be adjusted in real time. An excessive mass damper stroke may be introduced when the mass damper is subjected to a seismic excitation whose frequency content is within its operation range. The semi-active tuned mass damper (SATMD) has been proposed to solve this problem. The parameters of an SATMD can be adjusted in real time based on the measured structural responses and an appropriate control law. In this study, a stiffness-controllable TMD, called a leverage-type stiffness-controllable mass damper (LSCMD), is proposed and fabricated to verify its feasibility. The LSCMD contains a simple leverage mechanism and its stiffness can be altered by adjusting the pivot position. To determine the pivot position of the LSCMD in real time, a discrete-time direct output-feedback active control law that considers delay time is implemented. Moreover, an identification test for the transfer function of the pivot driving and control systems is proposed. The identification results demonstrate the target displacement can be achieved by the pivot displacement in 0-2 Hz range and the control delay time is about 0.1 s. A shaking-table test has been conducted to verify the theory and feasibility of the LSCMD. The comparisons of experimental and theoretical results of the LSCMD system show good consistency. It is shown that dynamic behavior of the LSCMD can be simulated correctly by the theoretical model and that the stiffness can be properly adjusted by the pivot position. Comparisons of experimental results of the LSCMD and passive TMD show the LSCMD with less demand on the mass damper stroke than that for the passive TMD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.50-55
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• 2021

Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1589-1597
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• 2021

Due to the low output rate and time delay of vehicle's navigation results, the electro-optical tracking system(EOTS) cannot estimate accurate target positions. If an inertial measurement unit(IMU) is additionally mounted into the EOTS and inertial navigation system(INS) is constructed, the high navigation output rate can be obtained. And the time-delay can be compensated by using the augmented Kalman filter. An accurate initial attitude is required in order to have accurate navigation outputs. In this paper, an attitude determination algorithm is proposed using the augmented Kalman filter in order to compensate measurement delay of the EOTS and have accurate initial attitude. The proposed initial attitude determination algorithm consists of an augmented Kalman filter, an INS, and an integrated Kalman filter. The augmented Kalman filter compensates the time-delay of the vehicle's navigation results and the integrated Kalman filter estimates the navigation error of the INS. In order to evaluate performance of the proposed algorithm, vehicle's navigation outputs and IMU measurements were generated using sensors' model-based measurement generator and initial attitude estimation errors of the proposed algorithm and the conventional algorithm without the augmented Kalman filter were compared for the generated measurements. The evaluation results show that the proposed algorithm has better accuracy.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.449-460
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• 2005

This paper proposes a method to track persons robustly in illumination changes and partial occlusions in color video frames acquired from a fixed camera. To solve a problem of changing appearance by illumination change, a time-independent intrinsic image is used to remove noises in an frame and is adaptively updated frame-by-frame. We use a hierarchical human model including body color information in order to track persons in occlusion. The tracked human model is recorded into a persons' list for some duration after the corresponding person's exit and is recovered from the list after her reentering. The proposed method was experimented in several indoor and outdoor scenario. This demonstrated the potential effectiveness of an adaptive model-base method that corrected distorted person's color information by lighting changes, and succeeded tracking of persons which was overlapped in a frame.