• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.115-117
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• 2009

This paper presents localization performance enhancement on GPS interfering spot for mobile robot. Localization system applied Extended Kalman filter algorithm that utilized Diffrential GPS and odometry, inertial sensors. In this paper, different noise covariance is applied to Extended Kalman Filter according to the GPS quality. Experiment results show that proposed localization system improve considerably localization performance of mobile robots.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.565-569
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• 2003

In this paper, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system with an integral quadratic constraint. We also derive the important characteristic of the proposed filter, a modified $H_{\infty}$ performance index. Analysis results show that the proposed filter has robustness against disturbances, such as process and measurement noises, and against parameter uncertainties. Simulation results show that the proposed filter effectively improves the performance.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.85-90
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• 2001

This work presents experimental results of filter media test by using particles from $0.02\;to\;0.6{\mu}m$ in diameter and by applying different charging states. In order to investigate the electret filter performance, the collection efficiency and the pressure drop of filter were measured. The face velocities of test filters varied from 2.4 to 20.4 cm/s. Another experiment setup for the cartridge cabin air filter was used to get an collection efficiency in submicron region. After charging level of electret filter severely decreased, the change of collection efficiency was verified. Experimental results show that the reliability of electret filters can be poor in some conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1450-1455
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• 2005

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure land DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.6-8
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• 2009

In this paper. we propose receiver algorithms for VHF(Very High Frequency) digital link mode-2(VDL Mode-2) systems. Unlike conventional digital communication systems using the root raised cosine filter as a transmit and receive filter, raised cosine filter is used as a transmit filter in VDL Mode-2 systems. Hence, it is crucial to design and implement the optimum lowpass receive filter by considering the amount of inter-symbol interference and noise performance. On the other hand, due to the short preamble pattern, it is crucial to develop an efficient packet detection algorithm for reliable communication link. In this paper, we design the optimum receive filter and packet detection algorithm and evaluate the performance of receiver adopting the proposed receive filter and packet detection algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.863-868
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• 2015

In this paper, the vibration of a single-wheel mobile robot is minimized by designing a filter. An AHRS (Attitude and heading reference system) sensor is used for measuring the state of the robot. The measured signals are analyzed using the FFT method to investigate the fundamental vibrational frequency with respect to the flywheel's speed of the gimbal system. The IIR notch filter is then designed to suppress the vibration at the identified frequency. After simulating the performance of the designated filter using the measured sensor data through extensive experiments, the filter is actually implemented in a single-wheel mobile robot, GYROBO. Finally, the performance of the designed filter is confirmed by performing the balancing control task of the GYROBO system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.74-76
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• 2017

In this paper, we introduce the CNN-based in-loop technology for HEVC, and analyze the performance of these algorithms through comparative experiments. The current in-loop filters in HEVC are composed of a deblocking filter that removes noise and a sample adaptive offset filter that compensates for signal offsets. A couple of CNN-based filters replacing the roles of these two algorithms are selected and compared.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.223-229
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• 2017

An angle error is a factor obstructing to track accurate position in tracking radars. And the noise incurring the angle error can be divided as follows; thermal noise and glint. In general, Extended Kalman filter used in tracking radars is designed with considering thermal noise only. The Extended Klaman filter uses a fixed measurement error covariance when updating an estimate state by using ahead state and measurement. But, a noise power varies according to the range. Therefore we purposes the adaptive Kalman filter which changes the measurement noise covariance according to the range. In this paper, we compare the performance of the Extended Kalman filter and the proposed adaptive Kalman filter by considering KSLV-I (Korean Satellite Launch Vehicles).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.188-190
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• 2012

Compressed Sensing (CS) has been developed for several years. Among many CS algorithms for image, the Block-based Compressed Sensing with Smoothed Projected Landweber (BCS-SPL) demonstrates its excellent performance in low-complexity and near-optimal reconstruction. Several noise filtering algorithms of image reconstruction have been introduced such as the Wiener or the median filters, etc. In general, each filter has its own advantages and disadvantages depending on specific coding scheme. In this paper, we show that reconstruction performance can be varied according to the choice of filter. When a sub-rate value is changed, different filter causes different effect as well. Concerning the sub-rate, an inner filter can be chosen to improve the reconstructed image quality.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.368-380
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• 2016

There is no doubt that adaptive optics (AO) is the most promising method to compensate wavefront disturbance in free space optics communication (FSO). In order to improve the performance of the AO system described by discrete-time linear system model with time-delay and implicit phase turbulent model, new controllers based on a Kalman filter and its extensions are proposed. Based on the standard Kalman filter, we propose a fading memory filter to deal with the ruleless strong interference; sequential and U-D filters are applied to reduce implementation complexity for the embedded controllers. Theoretical analysis and the numerical simulations show that the proposed fading memory filter can upgrade the performance for AO systems in consideration of the unforeseen strong pulse interference, and the sequential and U-D filters perform well compared with a Kalman filter.