• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.179-193
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• 2016

In power quality monitoring, voltage fluctuation is one of the power quality problems, which cause light flickers. To determine the flicker severity, the flicker meter concept was developed in an IEC 61000-4-15 standard. Generally, voltage fluctuations are described as an amplitude modulation(AM). The flicker meter of IEC 61000-4-15 as an international standard for flicker measurement recommends square demodulation method to detect flicker signals from voltage fluctuation signals. This paper suggests a new effective method using filter bank to detect and estimate flicker signals, which do not need square demodulation. For the accurate detection of flicker signals, the filter bank is designed with a full consideration of the spectrum characteristics of voltage fluctuation signals described as AM. The frequency and magnitude of the detected flicker signals are estimated using recursive method. Computer simulations were performed on synthesized signals to prove validity of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.621-626
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• 2005

With precise GPS carrier positioning result, we can get attitude information if GPS antenna has adequate attaching position on the vehicle. In this case, baseline length information can be bandied as an additional measurement or constraint. In this paper, we have proposed a method to improve the attitude accuracy. To overcome nonlinearity of baseline observation model, we analyze attitude estimation result using existing estimation method like a least square method and Kalman filter, and apply a new nonlinear estimation method an unscented Kalman filter Finally we confirm the improvement of attitude estimation result in the case of appling the unscented Kalman filter.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.103-109
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• 2013

The conventional LCL filter design method of the utility interactive inverter considers only harmonics attenuation of the current injected to the grid. However, in case of utility-interactive inverter with critical load the voltage quality of the critical load should also be considered for LCL filter design. Also, considering cost and volume of LCL filters. it is important to have minimum values of inductance and capacitance as far as the harmonic standards are satisfied. In this paper a LCL filter design method is proposed to satisfy not only the harmonic standards of the grid current during the grid-connected mode but the voltage quality of the critical load during grid-connected mode and stand-alone mode. With the proposed method optimized values of LCL filters could be obtained by applying weighting factor to voltage ripple across the critical load, inductor volume, amount of reactive current and system bandwidth.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.117-122
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• 2014

In CDGPS, ambiguity resolution is determined by the performance of a floating solution, and thus, the performance needs to be improved. In the case of precise positioning at a stationary position, the batch method using multiple measurements is used for the accuracy improvement of a position. The position accuracy performance of a floating solution is outstanding, but it has a problem of high computation cost because all measurements are used. In this study, to improve the floating solution performance of the initial static user in CDGPS, a floating solution method using a recursive filter was implemented. A recursive filter estimates the position solution of the current epoch using the position solution of up to the previous epoch and the pseudorange measurement of the current epoch. The computation cost of the floating solution method using a recursive filter was found to be similar to that of the epoch-by-epoch method. Also, based on actual GPS signals, the floating solution performance was found to be similar to that of the batch method. The floating solution using a recursive filter could significantly improve the performance of the prompt initial position and ambiguity resolution of the initial static user.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.141-148
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• 1998

We propose an efficient method of de-interlacing in the post-pocessing of HDTV signal. Since the proposed method considers human visual weight, it gives the better performance in the edge information preservation than that of the median filter. The processing time of the proposed method is twice faster than median filter, therefore the proposed method is suitable for the real-time de-interlacing in the post-processing of HDTV signal.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.3
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• pp.239-246
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• 2015

A novel control method of a three-phase PWM inverter with LC filter is proposed. The transfer function of LC filter is the same as that of second-order low pass filter(LPF), which has a zero damping ratio. A simple method of implementing second-order LPF with damping ratio is to add a resistor in an LC circuit. However, in a real power system, adopting damping resistors is impractical because it results in losses proportional to the square of the current flowing through the resistors. Instead of inserting resistors, the proposed control strategy utilizes the measured capacitor voltages to control the oscillation of LC circuit. The overall transfer function of the proposed method is the same as a second-order LPF, and its damping ratio is controllable via control variables. The current controller can have overshoots caused by LC filter. Improved current controller is implemented by an equivalent second-order of LC filter. A 7.5 kVA PWM converter and a PWM inverter with a 5.5 kW induction motor are set up to verify the proposed control algorithm. Test waveforms are also presented to verify the proposed LC filter control algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.986-991
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• 2014

The PPG signal used in mobile-healthcare and telemedicine system is including the various motion artifact that is signal generated from patient's movements. Recently, although the various methods to remove motion artifacts have been suggested, the performances of these methods are still not satisfactory. Therefore, this s study suggested the novel method based on the Kalman filter and adaptive filter to remove motion artifacts, and we used various motion artifacts to analyze the performance of the proposed method. In the results of experiments, the signal-to-noise ratio of proposed method showed good performace that was 4.8 times of moving average filter.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.1
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1331-1338
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• 2007

A new method for detecting and eliminating the Electrocardiogram(ECG) artifact from the scalp Electroencephalogram(EEG) is proposed. Based on the single channel EEG, the proposed method consists of 4 procedures: emphasizing the R-wave of ECG artifact from EEG using the least squares acceleration(LSA) filter, detecting the R-wave from the LSA filtered EEG using the phase space method and R-R interval, generating the delayed impulse synchronized to the R-wave and elimination of the ECG artifacts based on the adaptive digital filter using the impulse and raw EEG. The performance of the proposed method was evaluated in the two separating parts of R-wave detection and, ECG estimation and elimination from EEG. In the R-wave detection, the proposed method showed the mean error rate of 6.285(%). In the ECG estimation and elimination using simulated and/or real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, in which independent component analysis and ensemble average method are used. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifact from single channel EEG and simple for ambulatory/portable EEG monitoring system.