• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.7
• /
• pp.919-926
• /
• 2012

In order to control a LTI(Linear Time Invariant) system subjected to system noise and measurement noise, first of all, it is necessary to estimate the state of system with reliability. Kalman filtering technique has been widely used to estimate the state of the stochastic LTI system with stationary noise characteristics because of its estimation ability versus algorithm simplicity. However, it often fails to estimate the state of the LTI system of which system parameter uncertainty exists partly and/or input uncertainty exists. In this paper, a new estimation technique based on Kalman filter is suggested for stochastic LTI system under parameter uncertainty and/or input uncertainty. A fuzzy estimation algorithm against uncertainties is introduced so as to compensate the state estimate filtered by Kalman filter. In order to verify the state estimation performance of the suggested technique, several simulations are accomplished.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.6 s.99
• /
• pp.738-748
• /
• 2005

The ship radiated noise level fluctuates by the difference of interference and reverberation according to measurement methods and environmental conditions. These phenomena cause error of the source level estimation even in the same environment conditions. This paper describes a quantitative analysis and a reduction method for an error value to the source level estimation in spatial and temporal interference environment. The design criteria of the radiated noise measurement array composed of omni-directional hydrophones and the source level accuracy in the deep water range are given. The source level accuracy in the shallow water range is also derived based on the statistical model of the multiple reflection paths. The results are verified using the water tank experiment and the sea trial.

• Korean Journal of Remote Sensing
• /
• v.23 no.5
• /
• pp.455-464
• /
• 2007

Lee(2007) suggested the Point-Jacobian iteration MAP estimation(PJIMAP) for noise removal of the images that are corrupted by multiplicative speckle noise. It is to find a MAP estimation of noisy-free imagery based on a Bayesian model using the lognormal distribution for image intensity and an MRF for image texture. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. In this study, the MAP estimation is computed by the Point-Jacobian iteration using adaptive parameters. At each iteration, the parameters related to the Bayesian model are adaptively estimated using the updated information. The results of the proposed scheme were compared to them of PJIMAP with SAR simulation data generated by the Monte Carlo method. The experiments demonstrated an improvement in relaxing speckle noise and estimating noise-free intensity by using the adaptive parameters for the Ponit-Jacobian iteration.

• International Journal of Highway Engineering
• /
• v.15 no.3
• /
• pp.9-16
• /
• 2013

PURPOSES: There is a need to develop a method to incorporate tire-pavement noise in the pavement management system. Tire-pavement noise highly depends on the characteristics of pavement texture. Therefore, estimation of texture characteristics may give useful information to predict tire-pavement noise. This study aimed to find the relationship between tire-pavement noise and MPD(Mean Profile Depth) for concrete pavement. METHODS: MPD and tire-pavement noise were collected on the number of expressway sections including Central Inland Test Road in Korea. Statistical analysis was performed to find the correlationship between MPD and tire-pavement noise. In addition, multiple regression analysis to find the tire-pavement noise based on MPD and type of concrete pavement texture. RESULTS: Linear relationship between MPD and tire-pavement noise is observed for concrete pavement. Furthermore, a forensic equation to estimate tire-pavement noise based on MPD and texture types of concrete pavement is suggested. CONCLUSIONS: Tire-pavement noise on concrete pavement can be predicted based on the consideration of texture type and MPD estimation.

• Journal of Broadcast Engineering
• /
• v.13 no.5
• /
• pp.565-573
• /
• 2008

This paper proposes noise reduction methods to improve the channel estimation performance in Equalization On-Channel Repeater (E-OCR) for Terrestrial-Digital Multimedia Broadcasting (T-DMB) system. In the E-OCR for T-DMB system, the channel estimation is performed by the pilot signal extraction and the channel coefficient estimation. Since the performance of the channel estimation highly depends on the estimated channel coefficients whose accuracy is associated with the received signal-to-noise ratio (SNR), it is important to reduce noise existing at the estimated channel coefficients. To reduce such noise components, various noise reduction methods of the estimated channel coefficients based on the M -point weighted moving average are proposed. Computer simulations show that the proposed methods improve the estimation performance by more than 2 to 3 dB in terms of the symbol error rate after equalization.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.7
• /
• pp.767-773
• /
• 2014

The carrier-to-noise power ratio is a key parameter for determining the reliability of PVT (Position, Velocity, and Time) solutions which are obtained by a GNSS (Global Navigation Satellite System) receiver. It is also used for locking a tracking loop, deciding the re-acquisition process, and processing advanced navigation in the receiver subsystem. The representative carrier-to-noise power ratio estimation schemes are the narrowband-wideband power ratio method (NW), the MM (Moment Method), and Beaulieu's method (BL). The NW scheme is the most classical one for commercial GNSS receivers. It is often used as an authoritative benchmark for assessing carrier-to-noise power estimation schemes. The MM scheme is the least biased solution among them, and the BL scheme is a simpler scheme than the MM scheme. This paper focuses on the less biased estimation with low complexity when the residual phase noise remains, then proposes a novel carrier-to-noise power ratio estimation scheme with low complexity for GNSS receivers. The asymptotic bias of the proposed scheme is derived and compared with others, and the simulation results demonstrate that the complexity of the proposed scheme is lowest among them, while the estimation performance of the proposed scheme is similar to those of the BL and MM schemes in normal and high gained reception environments.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.7
• /
• pp.891-897
• /
• 2013

The power system frequency plays an important role in monitoring and controlling the power system. The frequency can be measured through discrete Fourier transform (DFT) coefficients of its positive fundamental frequency. The accuracy of the frequency estimate is severely affected by noise in the power system signal and the leakage effect of the negative fundamental frequency in DFT. This paper proposes a DFT-based frequency estimation algorithm to cope with the noise as well as the leakage effect. In this algorithm, two suitable digital filters are introduced to reduce efficiently frequency estimate error due to the noise. These filters are designed to use a digital bandpass filter and a second-degree integrator. The effectiveness of the proposed algorithm in reduction of frequency estimate error is verified through simulations on noise, harmonics and frequency deviation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3589-3605
• /
• 2018

In this paper, we investigate an individual channel estimation problem for multiple-input multiple-output (MIMO) two-way amplify-and-forward (AF) relay networks. To avoid self-interference during the estimation of the individual MIMO channels, a novel blind interference cancellation (BIC) approach is proposed based on an orthogonal preceding framework, where a pair of orthogonal precoding matrices is utilized at the source nodes. By designing an optimal decoding scheme, we propose to decompose the bidirectional transmission into a pair of unidirectional transmissions. Unlike most existing approaches, we make the practical assumption that the nonreciprocal MIMO channel and the mutual interference of multiple antennas are both taken into consideration. Under the precoding framework, we employ an orthogonal superimposed training strategy to obtain the individual MIMO channels. However, the AF strategy causes the noise at the terminal to be the sum of the local noise and the relay-propagated noise. To remove the relay-propagated noise during the estimation of the second-hop channel, a partial noise-nulling method is designed. We also derive a closed-form expression for the total mean square error (MSE) of the MIMO channel from which we compute the optimal power allocation. The simulation results demonstrate that the analytical and simulated curves match fully.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.806-811
• /
• 1994

Two kinds of static and dynamic state estimation methods are newly discussed for the problem of the measurement disturbance of environmental low-frequency noise in the presence of wind-induced noise. First, the probability characteristics of wind-induced noise are discussed in the form of probability distribution conditioned by wind speed, based on the simultaneous observation of the wind-induced noise and wind speed near a microphone. Next, especially form the viewpoint of simplicity for practical use, two kinds of static and dynamic state estimation methods are discussed. The static estimation method using the information on wind speed is fundamentally supported by the conservation principle of energy sum. The dynamic one is the method by using a recursive digital filter with the parameters successively renewed by the information on wind speed. This can be also simplified by using well-know Kalman filter under the assumption of the Gaussian distribution. The effectiveness of proposed two estimation methods are shown through experiments under a breezy condition in the open filed.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.4
• /
• pp.781-790
• /
• 2008

In order to improve on the divergence by noise convariance in the Kalman filter position estimation, we propose a method of position estimating through compensating the autonomous mobile robot's noise. Proposed method is the modified Kalman filter using neural network. It is prevented the divergence by the estimation of measurement noise covariance and system noise covariance. In order to verify the effectiveness of the proposed method, we performed simulations and experiments for position estimation. The results show that convergence and position error is reduced than the Kalman filter method.