• Journal of the Optical Society of Korea
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• v.17 no.6
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• pp.494-499
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• 2013

In this paper, we present an optical encryption and information authentication of 3D objects considering wireless channel characteristics. Using the optical encryption such as double random phase encryption (DRPE) and 3D integral imaging, a 3D scene with encryption can be transmitted. However, the wireless channel causes the noise and fading effects of the 3D transmitted encryption data. When the 3D encrypted data is transmitted via wireless channel, the information may be lost or distorted because there are a lot of factors such as channel noise, propagation fading, and so on. Thus, using digital modulation and maximum likelihood (ML) detection, the noise and fading effects are mitigated, and the encrypted data is estimated well at the receiver. In addition, using computational volumetric reconstruction of integral imaging and advanced correlation filters, the noise effects may be remedied and 3D information may be authenticated. To prove our method, we carry out an optical experiment for sensing 3D information and simulation for optical encryption with DRPE and authentication with a nonlinear correlation filter. To the best of our knowledge, this is the first report on optical encryption and information authentication of 3D objects considering the wireless channel characteristics.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.26-34
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• 1999

According to increase of nonlinear power electronics equipment, active power filters have been researched and developed for many years to compensate harmonic disturbances and reactive power. However the commercial of active power filter is being proceeded slowly, because the cost of active power filter compared to the passive filter for harmonic and reactive power compensation is expensive. Especially, the use of DSP (Digital Signal Processing) chip, which is frequently used to control 3-phase active power filter, is a factor of increasing the cost of active power filters. On the other hand, the use of only analog controller makes the controller's circuits much more complicate and depreciates the flexibilities of controller. In this paper, a controller with low cost for 5[kVA] 3-phase active power filter system is designed. To reduce the expense of active filter system, the presented controller is composed of digital control part using Intel 80C196KC $\mu$P and analog control part using hysteresis controller for current control. Characteristic analysis of designed controller for active filter system is performed by computer simulation and compensating characteristics of the designed controller are verified by experiment.tegy can apply to the vector control, leading to better output torque capability in the ac motor drive system. This strategy is that in the overmodulation range, the d-axis output current is given a priority to regulate the flux well, instead the q-axis output curent is sacrificed. Therefore, the vector control even in the overmodulation PWM operation can be achieved well. For this purpose, the d-axis output voltage of a current controller to control the flux is conserved. the q-axis output voltage to control the torque is controlled to place the reference voltage vector on the hexagon boundary in case of the overmodulation. The validity of the proposed overall scheme is confirmed by simulation and experiments for a 22[kW] induction motor drive system.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.75-88
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• 2009

The main purpose of the current research is to introduce the alternative algorithm of the non-recursive batch filter based on the unscented transformation in which the linearization process is unnecessary. The presented algorithm is applied to the orbit determination of a low earth orbiting satellite and compared its results with those of the well-known Bayesian batch least squares estimation and the iterative UKF smoother (IUKS). The system dynamic equations consist of the Earth's geo-potential, the atmospheric drag, solar radiation pressure and the lunar/solar gravitational perturbations. The range, azimuth and elevation angles of the satellite measured from ground stations are used for orbit determination. The characteristics of the non recursive unscented batch filter are analyzed for various aspects, including accuracy of the determined orbit, sensitivity to the initial uncertainty, measurement noise and stability performance in a realistic dynamic system and measurement model. As a result, under large non-linear conditions, the presented non-recursive batch filter yields more accurate results than the other batch filters about 5% for initial uncertainty test and 12% for measurement noise test. Moreover, the presented filter exhibits better convergence reliability than the Bayesian least squares. Hence, it is concluded that the non-recursive batch filter based on the unscented transformation is effectively applicable for highly nonlinear batch estimation problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.1
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• pp.1-8
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• 2016

In this study, we propose a control algorithm for Inertially Stabilized Platforms (ISP), which combines Disturbance Observer (DOB) with conventional proportional integral derivative (PID) control algorithm. A single axis ISP system was constructed using a direct drive motor. The joint friction was modeled as a nonlinear function of joint speed while the accuracy of the model was verified through experiments and simulation. In addition, various Q-filters, which have different orders and relative degrees of freedom (DOF), were implemented. The stability and performance of the ISP were compared through experimental study. The performance of the proposed PID-plus-DOB algorithm was compared with the experimental results of the conventional double loop PID control under artificial vehicle motion provided motion simulator with six DOF.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.10-16
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• 2012

Currently, the majority of systems which are non-linear are in need of the correct system equations for controlling and monitoring. Therefore, the correct estimation of parameters is crucial. Generally, parameters are changed due to system deterioration or sudden environmental alterations. Given the limitations of system monitoring unstable controls can arise. In the following paper, the parameter estimation method is proposed using software filters to combat these system instabilities. For dynamic instances, a powerful particle filter is used to control the nonlinear and noisy environments in which they take place. Using a setup simulation comprised of a slider and pendulum, the state variable of noise is obtained. After collecting the data, the proposed algorithm is used to estimate both the state variable and its parameters. Finally, these results are checked with correct parameter estimations to evaluate and verify the algorithms performance.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.1
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• pp.75-85
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• 2010

In this paper, a Z-source hybrid active power filter is proposed to compensate the harmonics and reactive power in power distribution system. The proposed system is composed of a 7th harmonics-tuned passive filter and an active power filter with a Z-source inverter topology, while voltage source PWM inverter or current source PWM inverter are applied as the power converter topology of conventional active power filters. The Z-source impedance network along with shoot through capability would ensure a constant DC voltage across the DC link. A polymer electrolyte membrane fuel cell is employed as an compensation DC energy source of the proposed system and its equivalent R-L-C circuit is modeled for simulation. As the compensation and control algorithm of the proposed system, the current synchronous detection algorithm is applied. The simulation analysis by PSIM is performed under the three-phase 220V/60Hz voltage source and 25A nonlinear diode loads. The effectiveness of the proposed the system is verified in the steady and transient states.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.99-107
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• 2018

In this paper, we study target tracking in two dimensional space using a Extended Kalman filter(EKF), various Extended Kalman Filter and Cost-Reference Particle Filter(CRPF), which can effectively estimate the state values of nonlinear measurement equation. We introduce various Extended Kalman Filter which the Unscented Kalman Filter(UKF), the Central Difference Kalman Filter(CDKF), the Square Root Unscented Kalman Filter(SR-UKF), and the Central Difference Kalman Filter(SR-CDKF). In this study, we calculate Mean Square Error(MSE) of each filters using Monte-Carlo simulation with unknown noise statistics. Simulation results show that among the various of Extended Kalman filter, Square Root Central Difference Kalman Filter has the best results in terms of speed and performance. And, the Cost-Reference Particle Filter has an advantageous feature that it does not need to know the noise distribution differently from Extended Kalman Filter, and the simulation result shows that the excellent in term of processing speed and accuracy.

• Smart Structures and Systems
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• v.4 no.6
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• pp.727-740
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• 2008

A down hole vertical seismic array is a sequence of instruments installed at various depths in the earth to record the ground motion at multiple points during an earthquake. Numerous studies demonstrate the unique utility of vertical seismic arrays for studying in situ site response and soil behavior. Examples are given of analyses made at two sites to show the value of data from vertical seismic arrays. The sites examined are the Lotung, Taiwan SMART1 array and a new site installed at Jingliao, Taiwan. Details of the installation of the Jingliao array are given. ARX models are theoretically the correct process models for vertical wave propagation in the layered earth, and are used to linearly map deeper sensor input signals to shallower sensor output signals. An example of Event 16 at the Lotung array is given. This same data, when examined in detail with a Bayesian inference model, can also be explained by nonlinear filters yielding commonly accepted soil degradation curves. Results from applying an ARMAX model to data from the Jingliao vertical seismic array are presented. Estimates of inter-transducer soil increment resonant frequency, shear modulus, and damping ratio are presented. The shear modulus varied from 50 to 150 MPa, and damping ratio between 8% and 15%. A new hardware monitoring system - TerraScope - is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The Pods are nominally 50 mm in diameter, and about 120 mm long. An internal 16-bit micro-controller oversees all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1980-1987
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• 1999

Restored image is always lower quality than original one due to distortion and noise. The purpose of image restoration is to improve the image quality by fixing the noise or distortion information. One category of spatial filters for image restoration is linear filter. This filter algorithm is easily implemented and can be suppressed the Gaussian noise effectively, but not so good performance for spot or impulse noise. In this paper, we propose the nonlinear spatial filter algorithm for image restoration called the optimal adaptive multistage filter(OAMF). The OAMF is used to reduce the filtering time, increases the noise suppression ratio and preserves the edge information. The OAMF optimizes the adaptive multistage filter(AMF) by using weight learning algorithm of back-propagation learning algorithm. Simulation results of this filter algorithm are presented and discussed.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.145-147
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• 2020

As deep learning technology advances, there have been many attempts to improve video codecs such as High-Efficiency-Video-Coding (HEVC) using deep learning technology. One of the most researched approaches is improving filters inside codecs through image restoration researches. In this paper, we propose a method 01 replacing the sample adaptive offset (SAO) filtering with a deep neural network. The proposed method uses the deep neural network to find the optimal offset value. The proposed network consists of two subnetworks to find the offset value and its type of the signal, which can restore nonlinear and complex type of error. Experimental results show that the performance is better than the conventional HEVC in low delay P and random access mode.