• 전자공학회논문지S
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• 제34S권2호
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• pp.52-62
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• 1997

To reconstruct the complete 3-D shape of an object, seveal range images form different viewpoints should be merged into a single model. The process of extraction of the transformation parameters between multiple range views is calle dregistration. In this paper, we propose a new algorithm to find the transformation parameters between multiple range views. Th eproposed algorithm consists of two step: initial estimation and iteratively update the transformation. To guess the initial transformation, we modify the principal axes by considering the projection effect, due to the difference fo viewpoints. Then, the following process is iterated: in order to extract the exact transformation parameters between the range views: For every point of the common region, find the nearest point among the neighborhood of the current corresponding point whose correspondency is defined by the reverse calibration of the range finder. Then, update the transformation to satisfy the new correspondencies. In order to evaluate the performance the proposed registration algorithm, some experiments are performed on real range data, acquired by space encoding range finder. The experimental results show that the proposed initial estimation accelerate the following iterative registration step.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4587-4605
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• 2019

High Efficiency Video Coding (HEVC) suffers from high computational complexity due to its quad-tree structure in motion estimation (ME). This paper exposes an adaptive search range decision algorithm for accelerating HEVC integer-pel ME on GPU which estimates the optimal search range (SR) using a MAP (Maximum A Posteriori) estimator. There are three main contributions; First, we define the motion feature as the standard deviation of motion vector difference values in a CTU. Second, a MAP estimator is proposed, which theoretically estimates the motion feature of the current CTU using the motion feature of a temporally adjacent CTU and its SR without any data dependency. Thus, the SR for the current CTU is parallelly determined. Finally, the values of the prior distribution and the likelihood for each discretized motion feature are computed in advance and stored at a look-up table to further save the computational complexity. Experimental results show in conventional HEVC test sequences that the proposed algorithm can achieves high average time reductions without any subjective quality loss as well as with little BD-bitrate increase.

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• 한국음향학회지
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• 제43권3호
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• pp.324-334
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• 2024

파면곡률거리추정(Wavefront Curvature Ranging, WCR)은 음파의 파면곡률로부터 음원의 거리를 추정하는 방법이다. 기존의 파면곡률거리추정은 음속을 상수로 가정하고 삼각법으로 거리를 추정한다. 이 가정 때문에 해저면반사경로가 뚜렷하게 분리되는 해양환경에서는 거리 오차가 발생한다. 거리 오차를 줄이기 위해 해양의 음속구조를 적용하고 최대우도추정(Maximum Likelihood Estimation, MLE)방법으로 거리를 추정하는 정합 파면곡률거리추정(Matched Wavefront Curvature Ranging, MWCR) 을 제안하였다. 정합 파면곡률거리추정의 시뮬레이션 결과로부터 거리 오차의 감소를 확인하였다. 향후에 실측 신호로부터 거리 추정의 신뢰성을 확인하면 소나 시스템에 적용 가능할 것이다.

• 한국항공우주학회지
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• 제31권1호
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• pp.58-66
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• 2003

본 논문에서는 무궁화위성을 대상으로 추적 안테나의 바이어스를 추정하기 위한 방안들을 제시하고 있다. 먼저 거리, 방위각, 앙각에 이어 선회시선거리를 포함하는 배치필터를 구성하였으며 시뮬레이션을 통하여 바이어스 추정성능 변화를 분석하였다. 또한 결과를 보완하기 위하여 정밀하게 보정된 타 추적 안테나의 정보를 이용하여 대상 안테나의 바이어스를 정확하게 예측하기 위한 방안을 제시하였다. 마지막으로 안테나 바이어스 추정 결과를 분석하고 평가할 수 있도록 안테나 바이어스간의 상관관계에 대한 분석을 수행하였다.

• 전자공학회논문지S
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• 제34S권8호
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• 한국음향학회지
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• 제30권3호
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• pp.129-135
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• 2011

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

• 한국인터넷방송통신학회논문지
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• 제14권6호
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• pp.113-117
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• 2014

본 논문에서는 레이더 시스템에서 탐지 거리 추정에 영향을 미치는 레이더 단면적의 크기에 대한 집적 방식을 비교 분석한다. 본 논문에서는 레이더 단면적의 크기에 따라 크기가 작을 경우 스웰링 케이스 1, 클 경우에는 스웰링 케이스 3의 탐지 확률을 레이더 방정식에 적용하여 탐지 거리를 추정하였다. 모의실험을 통해서 스웰링 케이스의 차이에 따른 코히런트 집적과 비 코히런트 집적을 비교 분석하였다. 비교 분석 결과, 비 코히런트 집적 방식이 추정 거리가 가장 우수하였고 코히런트 집적 방식은 스웰링 케이스를 적용한 탐지 거리 추정에 적합하지 않음을 알 수 있었다.

• 한국음향학회지
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• 제42권6호
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• pp.511-518
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• 2023

수중 이동체의 시험평가 과정에서 정확한 거리 추정은 중요한 요소 가운데 하나이다. 특히, 도달 시간 값을 이용하여 거리를 추정하는 경우 상관 특성 등으로 인해 처프 신호인 Linear Frequency Modulation(LFM)과 같은 신호의 적용성이 높다. 하지만 이동성이 있는 도플러 천이 환경에서는 거리-도플러 커플링 효과로 인하여 측정 오류가 발생할 수 있다. 이에 본 논문에서는 거리-도플러 커플링 효과를 보상하여 도달 시간 값의 측정 오류를 감소시키는 신호를 제시한다. 제안된 신호는 2종류의 LFM 신호를 중첩하여 구성하였으며, 거리-도플러 커플링 효과를 최소화할 수 있다. 시뮬레이션을 통해 제안된 신호가 수중 이동체의 거리 추정에 있어서 거리-도플러 커플링 효과를 보상하여 도달 시간 값의 측정 오류를 줄이는 방법임을 확인하였다.

• Communications for Statistical Applications and Methods
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• 제24권1호
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.