• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.2
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• pp.235-243
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• 2012

In this paper, we propose a method to improve performance of pilot symbol assisted modulation(PSAM) channel estimation method for OFDM systems over frequency selective channel. When channel values are estimated, the low pilot density used for channel estimation increases not only the effective data rate but also power efficiency. Thus, the lower pilot density which is used for channel estimation is better for OFDM system. At first, we estimate the channel values which are located at the middle of adjacent pilots, and then all of the possible channel values are estiamted by using original pilot values and previously estimated pilot values. Furthermore, the error of estimated channel values is reduced by introducing guard interval which is designed acccording to maximum channel delay. Performance achieved with the proposed method is illustrated by simulation experiments in comparison with the existing methods in terms of mean squared error(MSE).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.67-75
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• 2011

This paper presents a new test technique for evaluating performance of vehicle detectors with interval estimation, not the conventional point estimation, for presenting statistical confidence interval. The methodology is categorized into three parts; sampling plan, analysis on the characteristic of evaluation indices, and the expression of evaluation results. Even though many statistical sampling plans exist, stratified random sampling is regarded as the most appropriate one, considering the detector performance characteristics that varies with traffic, illumination, and meteorological conditions. No magic bullet exists for evaluation index for detector evaluation, hence the characteristics of evaluation indices were thoroughly analyzed and a reasonable process for choosing the best evaluation index is proposed. Finally, the methodology to express the result of detector evaluation for the entire evaluation period and individual analysis interval is represented, respectively. To overcome the existing drawbacks in point estimation, interval estimation by which statistical confidence interval can be represented is introduced for enhancing statistical reliability of traffic detector evaluation. This research can make vehicle detector scheme improve one step forward.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.987-994
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• 2011

From the point view of credit evaluation whose population is divided into the default and non-default state, two methods are considered to estimate conditional distribution functions: one is to estimate under the assumption that the data is followed the mixture normal distribution and the other is to use the kernel density estimation. The parameters of normal mixture are estimated using the EM algorithm. For the kernel density estimation, five kinds of well known kernel functions and four kinds of the bandwidths are explored. In addition, the corresponding ROC functions are obtained based on the estimated distribution functions. The goodness-of-fit of the estimated distribution functions are discussed and the performance of the ROC functions are compared. In this work, it is found that the kernel distribution functions shows better fit, and the ROC function obtained under the assumption of normal mixture shows better performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.9
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• pp.681-689
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• 2020

This paper presents methods and results of both flight test examining roll angle estimation performance of slowly rolling munition forced to spin in the air, and fabricating a replica of guided munition. Guided munition was deployed from multi rotor type UAV mother ship whose altitude and velocity was conveyed to it as initial state. Flight test scenario is composed of a sequence of munition drop(deployment), munition spin, roll angle estimation and stabilization. Munition was deployed from mother ship at around 200m high with horizontal velocity of 15m/s, and was made spun using internal reaction wheel. Performance analysis on roll angle estimation is provided in comparison with commercial aerospace graded GPS/INS. Moreover, several mechanisms that rotates munition using reaction wheel, and actual product that realizes one of them are introduced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.475-483
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• 2006

If channel coefficients errors exist in MIMO-OFDM systems, the performance degradation of systems will occurs. In order to improve the performance of MIMO-OFDM systems, the technique of obtaining accurate channel estimation in multipath fading channel is necessary. In this paper, we introduce and propose new channel estimation-modified ICA algorithm. Simulation results shows from BER and SER curves which compare the proposed algorithm under time-varying Rayleigh fading with perfect known channel. The result of channel estimation by the proposed algorithm in this simulation, it shows that PDF(amplitude of channel) are close to the case with perfect known channel at the receiver with respect to uncoded QPSK/16-QAM/64-QAM modulation. Also, we can see that BER and SER curves are very close to the case with perfect known channel. Therefore, we see that the proposed algorithm have a good performance in MIMO-OFDM systems.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.864-875
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• 2012

In this paper, we propose a carrier frequency offset estimation method for single-carrier MIMO systems. In the proposed method, phase rotated PN (Pseudo-Noise) sequences are transmitted to prevent a cancelling out of partial PN sequences. After removing a modulation of received PN sequences by multiplying of complex conjugated PN Sequences which are locally generated in receiver, a CFO (Carrier Frequency Offset) is accurately estimated by employing L&R method which is a kind of ML (Maximum Likelihood) estimation algorithm and uses multiple auto-correlatos. In addition, the frequency offset estimation scheme by using channel state information is proposed for accurate CFO estimation in time-varying Rayleigh channel. By performing computer simulations, MSE (Mean Square Error) performance of proposed method is almost same as MSE performance of SISO systems in AWGN channel. Moreover, MSE Performance of proposed method with using channel information is higher than MSE performances of SISO system and conventional method in time-varying Rayleigh channel.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1408-1418
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• 2007

In this paper, we analyze the performance of pilot symbol assisted channel estimation and equalization schemes for OFDM systems over frequency-selective time-varying channels and propose methods to improve the system performance. In the least square(LS) and linear minimum mean square error(MMSE) channel estimation, time domain windowing is introduced for banding the frequency domain channel matrix. The linear MMSE and decision feedback equalization schemes are employed with the pilot symbols for channel estimation taken into account in the equalization process. To reduce computational complexity, the band LU matrix factorization algorithm is introduced in solving the linear systems involved in the equalization, and the performances are compared with the known previous results by computer simulations. When time domain windowing is employed in the decision feedback equalization, the matrix related with the decision feedback process is shown to be unhanded and the resultant performance degradation is analyzed.

• Korean Journal of Metals and Materials
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• v.56 no.11
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• pp.813-821
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• 2018

The basic oxygen furnace (BOF) steelmaking process in the steel industry is highly complicated, and subject to variations in raw material composition. During the BOF steelmaking process, it is essential to maintain the carbon content and the endpoint temperature at their set points in the liquid steel. This paper presents intelligent models used to estimate the endpoint temperature in the basic oxygen furnace (BOF) steelmaking process. An artificial neural network (ANN) model and a least-squares support vector machine (LSSVM) model are proposed and their estimation performance compared. The classical partial least-squares (PLS) method was also compared with the others. Results of the estimations using the ANN, LSSVM and PLS models were compared with the operation data, and the root-mean square error (RMSE) for each model was calculated to evaluate estimation performance. The RMSE of the LSSVM model 15.91, which turned out to be the best estimation. RMSE values for the ANN and PLS models were 17.24 and 21.31, respectively, indicating their relative estimation performance. The essential input parameters used in the models can be selected by sensitivity analysis. The RMSE for each model was calculated again after a sequential input selection process was used to remove insignificant input parameters. The RMSE of the LSSVM was then 13.21, which is better than the previous RMSE with all 16 parameters. The results show that LSSVM model using 13 input parameters can be utilized to calculate the required values for oxygen volume and coolant needed to optimally adjust the steel target temperature.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.4
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• pp.120-130
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• 2019

In this study, based on the correlation between traffic volume data and vertical displacement data developed in previous research using the bridge maintenance big data of 2006, the vertical displacement estimation model using the traffic volume data of Gwangan Bridge for 10 years A comparison of the performance of the developed model with the current applicability is presented. The present applicability of the developed model is analyzed that the estimated displacement is similar to the actual displacement and that the displacement estimation performance of the model based on the structured regression analysis and the principal component analysis is not significantly different from each other. In conclusion, the vertical displacement estimation model using the traffic volume data developed by this study can be effectively used for the analysis of the behavior according to the traffic load of Gwangan Bridge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.103-108
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• 2023

We study the problem of selecting a subset of sensor nodes in sensor networks in order to maximize the performance of parameter estimation. To achieve a low-complexity sensor selection algorithm, we propose a greedy iterative algorithm that allows us to select one sensor node at a time so as to maximize the log-determinant of the inverse of the estimation error covariance matrix without resort to direct minimization of the estimation error. We apply QR factorization to the observation matrix in the log-determinant to derive an analytic selection rule which enables a fast selection of the next node at each iteration. We conduct the extensive experiments to show that the proposed algorithm offers a competitive performance in terms of estimation performance and complexity as compared with previous sensor selection techniques and provides a practical solution to the selection problem for various network applications.