• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.55-60
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• 2011

The most basic algorithm in SLAM(Simultaneous Localization And Mapping) technique of mobile robots is EKF(Extended Kalman Filter) SLAM. However, it requires prior information of characteristics of the system and the noise model which cannot be estimated in accurate. By this limit, Kalman Filter shows the following behaviors in a highly uncertain environment: becomes too sensitive to internal parameters, mathematical consistency is not kept, or yields a wrong estimation result. In contrast, $H_{\infty}$ filter does not requires a prior information in detail. Thus, based on a idea that $H_{\infty}$ filter based SLAM will be more robust than the EKF-SLAM, we propose a framework of $H_{\infty}$ filter based SLAM and show that suggested algorithm shows slightly better result man me EKF-SLAM in a highly uncertain environment.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.210-212
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• 2009

In object tracking based on the particle filter algorithm controlling the proper distribution of the samples is essential to accurately track the target. If the samples are spread too wide compared to the target size, the tracking accuracy may degrade as some samples can be caught by background clutters that is similar to the target. On the other hands if the samples are spread too narrow, the particle filter may fail to track the abrupt motion of the target. To solve this problem we propose an improved particle filter that adopts "re-weighting" technique at the observe step. We estimate the distribution of the weights of the current samples by its mean and variance. Then the samples are re-weighted so that the appropriate distribution of the samples in proportional to the target scale is obtained at the next select step. The proposed tracking method can avoid convergence to local mean and improve the accuracy of the estimated target state.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.111-117
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• 2004

The low-power design of the A/D converter is indispensable to achieve the compact bio-signal measuring device with long battery duration. In this paper, new decimation filter structure is proposed for the low-power design of the Sigma-Delta A/D converter in the bio-instruments. The proposed filter is based on the non-recursive structure of the CIC (Cascaded Integrator Comb) decimation filter in the Sigma-Delta A/D converter. By combining the CSD (Canonic Signed Digit) structure with common sub-expression sharing technique, the proposed decimation filter structure can significantly reduce the number of adders for implementation. For the fixed decimation factor of 16, the 15％ of power consumption saving is achieved in the proposed structure in comparison with that of the conventional polyphase CIC filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.973-976
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• 2009

Digital signal processing technique use to variety fields including communication. For these signal processing, FIR digital filter is representative. And for FIR digital filter designing, the window function is used to reduce the Gibbs phenomenon which occurs in the coefficient cutting process of the ideal filter. Therefore, in this paper to improve performance of digital filter, a high-order window function was applied. In this simulation, we compared a peak side-lobe and a transient characteristics with the existing window function.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.2 s.93
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• pp.128-133
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• 2005

An iris-coupled partial H-plane filter as a new type of partial H-plane filter is proposed. The proposed filter can be compared with conventional H-plane filter and uses an iris-type evanescent waveguide as a coupling structure. Filter design technique based on numerical simulation is developed to design and compare the proposed filter and H-plane filter. Designed iris-coupled partial H-plane filter has the same frequency response as that of the conventional H-plane filter while its cross section is one quarter. A good agreement between measurements and theoretical prediction is achieved.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.126-130
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion (FBFE) based on virus evolutionary genetic algorithm(VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter (EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FBFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by identifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.561-571
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• 2012

The MTF(Modulation Transfer Function) is one of quality assesment factors to evaluate the performance of satellite images. Image restoration is needed for MTF compensation, but it is an ill-posed problem and doesn't have a certain solution. Lots of filters were suggested to solve this problem, such as Inverse Filter(IF), Pseudo Inverse Filter(PIF) and Wiener Filter(WF). The most commonly used filter is a WF, but it has a limitation on distinguishing signal and noise. The L-curve-based Modified Wiener Filter(MWF) is a solution technique using a Tikhonov regularization method. The L-curve is used for estimating an optimal regularization parameter. The image restoration was performed with Dubaisat-1 images for PIF, WF, and MWF. It is found that the image restored with MWF results in more improved MTF by 20.93% and 10.85% than PIF and WF, respectively.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.595-604
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• 2011

A three-phase three-level shunt active filter controlled by fuzzy logic current controller which can compensate current harmonics generated by nonlinear loads is presented. Three-level inverters and fuzzy controllers have been successfully employed in several power electronic applications these past years. To improve the conventional pwm controller performance, a new control scheme based on fuzzy current controller is adopted for three-level (NPC) shunt active filter. The scheme is designed to improve compensation capability of APF by adjusting the current error using a fuzzy rule. The inverter current reference signals required to compensate harmonic currents use the synchronous reference detection method. This technique is easy to implement and achieves good results. To maintain the dc voltage across capacitor constant and reduce inverter losses, a proportional integral voltage controller is used. The simulation of global system control and power circuits is performed using Matlab-Simulink and SimPowerSystem toolbox. The results obtained in transient and steady states under various operating conditions show the effectiveness of the proposed shunt active filter based on fuzzy current controller compared to the conventional scheme.