• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.3
• /
• pp.315-321
• /
• 2023

In this paper, we propose an algorithm that jointly estimates the location and velocity of a near-field moving target in a pulse radar system. The proposed algorithm estimates the location and velocity corresponding to the outcome of orthogonal matching pursuit (OMP) in a 4-dimensional (4D) location-velocity space. To address the high computational complexity of 4D parameter joint estimation, we propose an algorithm that iteratively estimates the target's 2D location and velocity sequentially. Through simulations, we analyze the estimation performance and verify the computational efficiency of the proposed algorithm.

• Tunnel and Underground Space
• /
• v.12 no.1
• /
• pp.10-18
• /
• 2002

Rock joint system makes a heavy effect on the behavior of rock structures. The definition of a 3D rock joint system is very important in 2D or 3D numerical analysis for the prediction of the behavior of a discontinuous rock mass. To enhance the reality of a 3D definition of rock joint system, it is essential to estimate the unbiased statistics of basic geometric attributes of rock joints. In this study, we have proposed the statistical analysis and derived the related equations for an estimation of statistics of joint size and intensity. Geometry of rock joints in 3 dimensional space can be defined by the aggregate of location, size, orientation and intensity. The dimensional limit of survey method and its data makes 3D geometric attributes probabilistic. In the estimation of statistics of joint size, we have discussed the technique to correct the bias from a dimensional limit and derived the equation of 3D joint intensity by stereological approaches.

• Tunnel and Underground Space
• /
• v.29 no.2
• /
• pp.89-107
• /
• 2019

Rock joints have an extremely important role in analyzing the mechanical stability and hydraulic characteristics of rock mass structures. Most rock joint parameters are generally indicated as a distribution by statistical techniques. In this research, calculation technique of Joint Center Volume (JCV) is analyzed, which is required for estimating the size distribution having the largest uncertainty among the joint parameters, then a new technique is proposed which is applicable regardless of the shape of survey window. The existing theoretical JCV calculation technique can be applied only to the plane window, and the complete enumeration techniques show the limitations in joint trace type and analysis time. This research aims to overcome the limitations in survey window shape and joint trace type through calculating JCV by using Monte Carlo simulation. The applicability of proposed technique is validated through the estimation results at non-planar survey windows such as curved surface and tunnel surface.

• Communications for Statistical Applications and Methods
• /
• v.3 no.2
• /
• pp.37-42
• /
• 1996

Maximum likelihood estimation of Cholesky decomposition is considered under normality assumption. It is shown that maximum liklihood estimation gives a Cholesky decomposition of the sample covariance matrix. The joint distribution of the maximum likelihood estimators is derived. The ussual algorithm for a Cholesky decomposition is shown to be equivalent to a maximumlikelihood estimation of a Cholesky root when the underlying distribution is a multivariate normal one.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5860-5876
• /
• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• Journal of Broadcast Engineering
• /
• v.26 no.5
• /
• pp.519-532
• /
• 2021

Recently, in various fields such as games, movies, and animation, content that uses motion capture to build body models and create characters to express in 3D space is increasing. Studies are underway to generate animations using RGB-D cameras to compensate for problems such as the cost of cinematography in how to place joints by attaching markers, but the problem of pose estimation accuracy or equipment cost still exists. Therefore, in this paper, we propose a system that inputs RGB images into a joint estimation network and converts the results into 3D data to create FBX format animations in order to reduce the equipment cost required for animation creation and increase joint estimation accuracy. First, the two-dimensional joint is estimated for the RGB image, and the three-dimensional coordinates of the joint are estimated using this value. The result is converted to a quaternion, rotated, and an animation in FBX format is created. To measure the accuracy of the proposed method, the system operation was verified by comparing the error between the animation generated based on the 3D position of the marker by attaching a marker to the body and the animation generated by the proposed system.

• Communications for Statistical Applications and Methods
• /
• v.15 no.5
• /
• pp.719-726
• /
• 2008

In this paper we consider a joint test for seasonal cointegrating(CI) ranks that enables us to simultaneously model cointegrated structures across seasonal unit roots in seasonal cointegration. A CI rank test for a single seasonal unit root is constructed and extended to a joint test for multiple seasonal unit roots. Their asymptotic distributions and selected critical values for the joint test are obtained. Through a small Monte Carlo simulation study, we evaluate performances of the tests.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.38 no.3
• /
• pp.9-18
• /
• 2001

In this paper, we present the joint symbol detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system in fading channels. The proposed methods are based on decision-directed channel estimation (DDCE) method and their symbol detection is achieved by using Viterbi algorithm. This Viterbi decision-directed channel estimation (VDDCE) method tracks time-varying channels and detects a maximum likelihood symbol sequence. Recursive Viterbi decision-directed channel estimation (RVDDCE) method based on VDDCE method is proposed to shorten the detecting depth. In this method, channel estimate and Viterbi processing are recursively performed every interval of training symbol. Also, average chann'el estimation (ACE) technique to reduce the effect of additive white Gaussian noise (AWGN) is applied VDDCE method and RVDDCE method. These proposed methods arc demonstrated by computer simulation.

• Journal of Sensor Science and Technology
• /
• v.29 no.4
• /
• pp.237-242
• /
• 2020

This paper deals with relative position estimation using a Kalman filter (KF) based on inertial sensors that have been widely used in various biomechanics-related outdoor applications. In previous studies, the relative position is determined using relative orientation and predetermined segment-to-joint (S2J) vectors, which are assumed to be constant. However, because body segments are influenced by soft tissue artifacts (STAs), including the deformation and sliding of the skin over the underlying bone structures, they are not constant, resulting in significant errors during relative position estimation. In this study, relative position estimation was performed using a KF, where the S2J vectors were adopted as time-varying states. The joint constraint and the variations of the S2J vectors were used to develop a measurement model of the proposed KF. Accordingly, the covariance matrix corresponding to the variations of the S2J vectors continuously changed within the ranges of the STA-causing flexion angles. The experimental results of the knee flexion tests showed that the proposed KF decreased the estimation errors in the longitudinal and lateral directions by 8.86 and 17.89 mm, respectively, compared with a conventional approach based on the application of constant S2J vectors.