• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.1004-1010
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• 2012

In this paper, we propose the algorithm which considers applying recently proposed clock synchronization techniques with quite high accuracy in a few wireless sensor networks researches to time synchronization algorithm for multi-static radar system and especially overcomes the limitation of previous theory, cannot be applied between nodes in non-line of sight (NLOS). Proposed scheme estimates clock skew and clock offset using recursive robust least M-estimator with information of time stamp observations. And we improve the performance of algorithm by tracking and suppressing the time delays difference caused by NLOS system. Futhermore, this paper derive the mean square error (MSE) to present the performance of the proposed estimator and comparative analysis with previous methods.

• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.156-162
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• 2018

The LMF (Least Mean Fourth) algorithm is well known for its fast convergence and low steady-state error especially in non-Gaussian noise environments. Recently, there has been increasing interest in the LMS (Least Mean Square) algorithms with self-adjusted step size. It is because the self-adjusted step-size LMS algorithms have shown to outperform the conventional fixed step-size LMS in the various situations. In this paper, a self-adjusted step-size LMF algorithm is proposed, which adopts an averaged gradient based step size as a self-adjusted step size. It is expected that the proposed algorithm also outperforms the conventional fixed step-size LMF. The superiority of the proposed algorithm is confirmed by the simulations in the time invariant and time variant channels.

• Journal of IKEEE
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• v.15 no.3
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• pp.235-240
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• 2011

The scattered pilots employed in DVB-T take advantage of the merits of both the block type and comb type pilot arrangement to increase the transmission efficiency. To estimate the channel transfer functions for data subcarriers, it is required to conduct time-frequency domain 2D estimation using the pilots. Though 2D Wiener estimator is optimal in sense of MSE (mean square error), it is too complex to implement in hardware. In this paper a new channel estimation method for the scattered pilot based OFDM system by measuring the power of AWGN and removing the noise in the LS (least square) estimate of the channel is proposed. And the simulation results reveal the proposed method outperforms the 2D linear interpolation in the fading channel.

• Journal of KSNVE
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• v.10 no.5
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• pp.886-891
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• 2000

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 estimated polynomial shape model is then used for calculating the hydrophone positions on the assumption that the arc distances between sensors are constant. In order to verify the applicability of the proposed algorithm, numerical simulations are performed using two types of non-linear array shapes. In addition the noise effects of heading sensors on the array shape estimation results and the performance of beamformer are also investigated.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.14-20
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• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1465-1474
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• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12A
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• pp.1174-1182
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• 2005

This paper, we propose a new channel Estimation method for MB-OFDM(Multi-Band OFDM) system that is suggested as one of standards in IEEE 802.15 TG3a for high data rate(110Mbps${\~}$480Mbps) WPAN system. The proposed method uses correlation characteristic of the PS(Packet Synchronization) sequence for timing synchronization. It can reduce the influence of noise compared with the conventional algorithm which based on LS(Least square) algorithm is redundancy without using the CE(Channel Estimation) Sequence for channel Estimation. We simulate both conventional method and proposed method for performance analysis in S-V channel environment which proposed by IEEE 802.15.3a. Simulation results show the proposed algorithm outperforms conventional algorithm about 1${\~}$1.5dB of Eb/NO.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.166-173
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• 2005

In this paper, we propose a mobile channel estimation algorithm using matching pursuit algorithm for orthogonal frequency division multiplexing (OFDM) systems. Least square (LS) algorithm, which is used as a conventional channel estimation algorithm for OFDM systems, has error probability of channel estimation affected by effects of noise. By estimating the channel of sparse type, the proposed algorithm reduces effects of noise during time intervals that multi-path signal doesn't exist. The proposed algorithm estimates a mobile receivingchannel using pilot information transmitted consequently. We compare performance of the proposed algorithm with the LS algorithm by measuring symbol error rate with 64QAM under a mobile multi-path fading channel model.