• The Journal of the Acoustical Society of Korea
• /
• v.15 no.1
• /
• pp.34-39
• /
• 1996

Target state estimation is a fundamental problem of the sonar signal processing. In this paper, the covariance analysis techniques are applied to enhance the performance of the target state estimation of a monopulse sonar system. MOST, the artificial target signal generator based on the highlight model is used to generate signals in various target states. The performance of the developed method has been evaluated by applying it to the various S/N. The enhanced performance of the covariance analysis method presented in this paper is discussed.

• Structural Engineering and Mechanics
• /
• v.56 no.5
• /
• pp.767-785
• /
• 2015

The stochastic finite element method is employed to obtain a stochastic dynamic model of angled beams subjected to impact loads when uncertain material properties are described by random fields. Using the perturbation technique in conjunction with a precise time integration method, a random analysis approach is developed for efficient analysis of random elastic waves. Formulas for the mean, variance and covariance of displacement, strain and stress are introduced. Statistics of displacement and stress waves is analyzed and effects of bend angle and material stochasticity on wave propagation are studied. It is found that the elastic wave correlation in the angled section is the most significant. The mean, variance and covariance of the stress wave amplitude decrease with an increase in bend angle. The standard deviation of the beam material density plays an important role in longitudinal displacement wave covariance.

• The Korean Journal of Applied Statistics
• /
• v.35 no.4
• /
• pp.569-577
• /
• 2022

Simulation studies are often conducted when it is difficult to compare the performance of nonparametric estimators theoretically. Kim and Kim (2021) showed that more systematic and accurate comparisons can be made if you analyze the simulation results using a regression model,. This study is a complementary study on Kim and Kim (2021). In the variance-covariance matrix for the error term of the regression model, only heteroscedasticity was considered and covariance was ignored in the previous study. When covariance is considered together with the heteroscedasticity, the variance-covariance matrix becomes a block diagonal matrix. In this study, a method of estimating and using the block diagonal variance-covariance matrix for the analysis was presented. This allows you to find more pairs of estimators with significant performance differences while ensuring the nominal confidence level.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.45-49
• /
• 1989

The observability of an strapdown inertial navigation system(SDINS) is investigated. The piece-wise constant systems are defined and the stepped observability matrix scheme is applied to observability analysis of SDINS theoretically, the results are compared with that of covariance simulation. It is found that SDINS is more observable than gimballed inertial navigation system (GINS) in the case of the variation of vehicle attitude, and is found that the stepped observability matrix theory is simple and useful for the analysis of the system observability but the results are not completely same as that of covariance simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.53-57
• /
• 1998

Star tracker placement configuration is proposed and the properness of the placement configuration is verified for star tracker's sun avoidance angle requirement. Precision attitude determination system is successfully designed using a gyro-star tracker inertial reference system for a candidate LEO spacecraft. Elaborate kalman filter formulation for a spacecraft is proposed for covariance analysis. The covariance analysis is performed to verify the capability of the proposed attitude determination system. The analysis results show that the attitude determination error and drift rate error are good enough to satisfy the mission of a candidate spacecraft.

• Atmosphere
• /
• v.20 no.3
• /
• pp.287-306
• /
• 2010

An ensemble Kalman filter (EnKF) with Weather Research and Forecasting (WRF) Model is applied for Typhoon Wukong (200610) to investigate the performance of ensemble forecasts depending on experimental configurations of the EnKF. In addition, the ensemble sensitivity analysis is applied to the forecast and analysis ensembles generated in EnKF, to investigate the possibility of using the ensemble sensitivity analysis as the adaptive observation guidance. Various experimental configurations are tested by changing model error, ensemble size, assimilation time window, covariance relaxation, and covariance localization in EnKF. First of all, experiments using different physical parameterization scheme for each ensemble member show less root mean square error compared to those using single physics for all the forecast ensemble members, which implies that considering the model error is beneficial to get better forecasts. A larger number of ensembles are also beneficial than a smaller number of ensembles. For the assimilation time window, the experiment using less frequent window shows better results than that using more frequent window, which is associated with the availability of observational data in this study. Therefore, incorporating model error, larger ensemble size, and less frequent assimilation window into the EnKF is beneficial to get better prediction of Typhoon Wukong (200610). The covariance relaxation and localization are relatively less beneficial to the forecasts compared to those factors mentioned above. The ensemble sensitivity analysis shows that the sensitive regions for adaptive observations can be determined by the sensitivity of the forecast measure of interest to the initial ensembles. In addition, the sensitivities calculated by the ensemble sensitivity analysis can be explained by dynamical relationships established among wind, temperature, and pressure.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.14 no.2
• /
• pp.23-31
• /
• 2006

Tolerance analysis of auto body requires the consideration of its compliance because of potentially significant deformation during the spot-weld assembly process. In this paper, a relatively recent method for such analyses is briefly introduced as one can find in the literature. In this method, it is important to take into account of the covariance between the sources of variation as they are closely located, which is the case in most auto body assembly. However, it is often impossible to know such covariance, for example, when a new car is being developed. Therefore, a mechanics-based method is proposed in this paper to estimate the covariance among the sources of variation by finite element analyses and simple statistical computations. The proposed method is illustrated by applying it to a three-dimensional model of real front wheel housing.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.1E
• /
• pp.26-32
• /
• 2003

We propose new time-frequency (TF) tools for analyzing linear time-varying (LTV) systems and nonstationary random processes showing hyperbolic TF structure. Obtained through hyperbolic warping the narrowband Weyl symbol (WS) and spreading function (SF) in frequency, the new TF tools are useful for analyzing LTV systems and random processes characterized by hyperbolic time shifts. This new TF symbol, called the hyperbolic WS, satisfies the hyperbolic time-shift covariance and scale covariance properties, and is useful in wideband signal analysis. Using the new, hyperbolic time-shift covariant WS and 2-D TF kernels, we provide a formulation for the hyperbolic time-shift covariant TF symbols, which are 2-D smoothed versions of the hyperbolic WS. We also propose a new interpretation of linear signal transformations as weighted superposition of hyperbolic time shifted and scale changed versions of the signal. Application examples in signal analysis and detection demonstrate the advantages of our new results.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.1
• /
• pp.83-88
• /
• 2009

This paper consider the problem of direction of arrival(DOA) estimation in the presence of multipath propagation. The sensor elements are assumed to be linear and uniformly spaced. Numerous authors have advocated the use of a beamforming preprocessor to facilitate application of high resolution direction finding algorithms The benefits cited include reduced computation, improved performance in environments that include spatially colored noise, and enhanced resolution. Performance benefits typically have been demonstrated via specific example. The purpose of this paper is to provide an analysis of a beamspace version of the MUSIC algorithm applicable to two closely spaced emitters in diverse scenarios. Specifically, the analysis is applicable to uncorrelated far field emitters of any relative power level, confined to a known plane, and observed by an arbitrary array of directional antenna. In this paper, we researched about optimize beam forming to smart antenna system. The covariance matrix obtained using fourth order cumulant function. Simulations illustrate the performance of the techniques.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.2
• /
• pp.345-353
• /
• 1994

This paper proposes a high resolution direction finding method, which is so called the 'averaged MUSIC'. This method uses a new sample array covariance matrix that consists of diagonal components obtained by taking averages of the diagonal component values of the sample covariance matrix for the MUSIC. This paper also shows that the proposed method performs higher resolced direction-of-arrival estimation than the MUSIC in such cases as low signal-to-noise ratio, closed signal sources, and limited number of sensors, based on the statistical analysis.