• Journal of IKEEE
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• v.16 no.3
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• pp.211-216
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• 2012

In the phase boundary estimation problem, the estimation performance depends on the initial guess. However, there is no information on the number of bubbles and those positions for the initial guess in real flows. Therefore, it is very important to set appropriate initial guesses from prior information. In this paper, in order to set initial guesses for estimating the phase boundaries in two-phase flows, first, unknown resistivity distribution was estimated using the difference reconstruction method. After that, an adaptive threshold value was automatically computed using intermodes method. Based on this value, the number of bubbles and the initial position were determined. The numerical experiments have been performed to evaluate the estimation performance of the proposed method.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1085-1091
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• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.74-80
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• 2001

Because of ocean waves, swell, steering corrections, etc, the hydrophones of a towed array will not live along a straight line. However the degradation of bearing estimation performance occurs when beamforming is carried out on the hydrophone outputs of an acoustic towed array which is not straight. So it is required to estimate the shape of the array for the improved beamformer output. In this paper, an iterative array shape estimation technique is presented, which is based on the use of the least squares polynomial fitting to the data from heading sensors. The estimation error and the influence of deformations on the performance of the conventional beamformer output are investigated. Finally, the suggested method is applied to the real system in order to investigate the applicability.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.1-9
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• 2010

In this paper, we propose a new method of improving accuracy of motion estimation in mobile environments, compared with Rosten's algorithm. The present method selects corners as feature points. The Rosten's algorithm uses simple addition and subtraction to detect the corners. Although it has the advantage of faster processing speed, Rosten's algorithm has a drawback of low performance in motion estimation. We use the NCC(Normalized Cross Correlation) coefficients to match the corners, and remove in two steps the outliers of inaccurate matching corners. We compare the proposed algorithm with Rosten's algorithm by applying both to the real images. We find that the proposed method shows better performance than Rosten's algorithm in motion estimation. In addition, we implement the present method on mobile devices and confirm that it works in mobile environments in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.391-397
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• 2011

This paper investigates the frequency offset (PO) estimation scheme for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems. In the CR environments, the conventional FO estimation schemes for the OFDM systems experience significant performance degradation due to the effect of the non-Gaussian noise. In this paper, a novel FO estimation scheme based on the maximum likelihood criterion is proposed for the OFDM-based CR systems in non-Gaussian noise environments. The proposed scheme does not require a specific pilot structure and has a better estimation performance compared with that of the conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.234-241
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• 2009

TETRA Enhanced Data Service (TEDS), which is an upgrade version of narrow-band ETSI TETRA Release 1 system, can support high speed packet data services in frequency selected fading channel. The performance of M-QAM transceivers employed in the TEDS is significantly affected by the accuracy of channel estimation. In this paper, we consider the design of a decision-directed channel estimation scheme robust to fast fading by estimating the channel by means of a per-survivor processing (PSP) method. The performance of the proposed channel estimation scheme is verified by computer simulation.

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.