• 한국통신학회논문지
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• 제32권4C호
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• pp.418-424
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• 2007

본 논문에서는 null 부반송파를 갖는 OFDM 시스템에서 단순화된 시간 영역 채널 추적(tracking) 방식을 제안하였다. 제안된 채널 추적 방식은 결정 귀환된 데이터를 이용하여 간단한 주파수 영역 채널 추정을 먼저 수행함으로써 시간 영역 채널 추정을 간략화한 방식이다. 제안된 방식은 기존의 시간영역 채널 추정 방식 보다 계산량 면에서 약 93% 정도 감소한다. 본 논문에서 성능 분석은 추정된 채널 응답의 MSE 성능과 수신기의 BER 성능면에서 이루어졌다. 시뮬레이션 결과 제안된 방식은 줄어든 계산량에도 불구하고 기존의 시간 영역 채널 추적 방식과 동일한 성능을 보였다.

• 한국음향학회지
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• 제20권8호
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• pp.58-66
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• 2001

본논문에서는 LFM (Linear Frequency Modulated) 신호를 사용하는 능동소나에서 적은 연산량으로 표적반사신호의 시간지연과 도플러를 추정하는 기법을 제안하였다. 제안한 기법에서는 일반적인 추정기법들이 가지는 연산량의 문제를 해결하기 위해 LFM 신호의 상호모호함수 (cross ambiguity function)에서 시간지연과 도플러의 관계를 나타내는 대수적인 관계식을 이용하였다. FML (Fast Maximum Likelihood) 기법을 기반으로 하여 시간지연과 도플러의 대수적 관계식을 유도하였으며, 이를 이용하여 일반적인 2차원 탐색 대신 2번의 1차원 탐색으로 시간지연과 도플러를 추정하였다. 다양한 신호대 잡음비 (SNR)에서 제안한 알고리즘의 추정오차를 분석하였으며, 제안한 알고리즘이 우수한 추정 성능을 보임을 확인하였다.

• 한국통신학회논문지
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• 제34권8C호
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• pp.814-821
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• 2009

초광대역 방식의 실내 무선 위치인식 추정에서 비 가시거리 환경으로 인한 불규칙한 신호 도착시간 또는 클러스터화 된 다중경로 성분들의 겹침으로 인해, 도착시간 매개변수 추정 기법들은 합리적인 도착시간 (TOA) 매개변수를 얻는데 어려움을 가진다. 이 문제를 극복하고 우수한 성능의 초광대역 실내 우선 위치인식 추정을 달성하기 위해 종래 추정 기법과 다르고 클리스터 문제에 영향을 거이 받지 않는 강인한 TOA 매개변수 추정 기법과 초광대역 신호 모형을 제안한다. 컴퓨터 모의실험을 통해 제안 모형과 추정기법의 타당성을 검증하고 추정오차의 성능도 분석한다.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.702-708
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• 2019

This paper deals with break size estimation of loss of coolant accidents (LOCA) using a nonlinear autoregressive with exogenous inputs (NARX) neural network. Previous studies used static approaches, requiring time-integrated parameters and independent firing algorithms. NARX neural network is able to directly deal with time-dependent signals for dynamic estimation of break sizes in real-time. The case studied is a LOCA in the primary system of Bushehr nuclear power plant (NPP). In this study, number of hidden layers, neurons, feedbacks, inputs, and training duration of transients are selected by performing parametric studies to determine the network architecture with minimum error. The developed NARX neural network is trained by error back propagation algorithm with different break sizes, covering 5% -100% of main coolant pipeline area. This database of LOCA scenarios is developed using RELAP5 thermal-hydraulic code. The results are satisfactory and indicate feasibility of implementing NARX neural network for break size estimation in NPPs. It is able to find a general solution for break size estimation problem in real-time, using a limited number of training data sets. This study has been performed in the framework of a research project, aiming to develop an appropriate accident management support tool for Bushehr NPP.

• 한국음향학회지
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• 제37권6호
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• pp.499-505
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• 2018

서로 떨어져 설치된 두 개의 음향 센서에 도달하는 신호의 상호 지연 시간을 추정하는 것은 실내 음향과 소나 등에서 목표물 위치 추정 문제나 추적 및 동기화에 이르기까지 다방면에서 쓰이고 있다. 시간 지연을 구하는 방법에서는 두 수신 신호 사이의 상호 상관을 이용한 방법이 대표적이다. 그러나 이 방법은 수신 음향 센서에 잡음이 부과 되는 것에 충분한 고려가 없었다. 본 논문은 수신 음향 센서에 모두 잡음이 부과된 경우를 고려한 새로운 시간 지연 추정 방법을 제안한다. 기존의 일반 상호 상관법과 적응 고유치 분석법과 비교를 통해서 새로 제안한 알고리즘이 유색 신호에 부가된 가우시안 잡음환경에서 우수성이 있음을 확인한다.

• Journal of Astronomy and Space Sciences
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• 제41권2호
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• pp.61-78
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• 2024

This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1063-1075
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• 2012

To locate an object accurately in the wireless sensor networks, the distance measure based on time-delay plays an important role. In this paper, we propose a maximum likelihood (ML) time-delay estimation algorithm in multi-path wireless propagation channel. We get the joint probability density function after sampling the frequency domain response of the multi-path channel, which could be obtained by the vector network analyzer. Based on the ML criterion, the time-delay values of different paths are estimated. Considering the ML function is non-linear with respect to the multi-path time-delays, we first obtain the coarse values of different paths using the subspace fitting algorithm, then take them as an initial point, and finally get the ML time-delay estimation values with the pattern searching optimization method. The simulation results show that although the ML estimation variance could not reach the Cramer-Rao lower bounds (CRLB), its performance is superior to that of subspace fitting algorithm, and could be seen as a fine algorithm.

• 대한의생명과학회지
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• 제12권4호
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• pp.439-442
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• 2006

To evaluate the postmortem changes in activities of oxygen free radical metabolizing enzymes, the rats were sacrificed with cervical dislocation and were kept in an incubator at $25^{\circ}C$, 70% of humidity for 12 hours. The activities of aniline hydroxylase, catalase, glutathione-S-transferase and superoxlde dismutase were decreased with the time. On the other hand, the activity and type conversion ratio (type D ${\to}$type O) of hepatic xanthine oxidase (XO) were gradually increased. From these changes of XO, the estimation of death time (mathematical equation) could be determined with the least square method. To clarify the cause of increasing XO activity, enzyme kinetics were examined. The Km values of XO were decreased with the time. In conclusion, the determination of liver XO activity might be used for the estimation of death time in the early postmortem period.

• Journal of Communications and Networks
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• 제5권2호
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• pp.167-173
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• 2003

We treat the problem of channel estimation and interference cancellation in multiuser ultra-wide-band (UWB) communication systems over multipath fading channels. The UWB system under consideration employs a random time-hopping impulse radio format. We develop a channel estimation method based on linear weighted algorithm. An iterative channel estimation and interference cancellation scheme is proposed to successively improve the receiver performance. We also consider systems employing multiple transmit and/or receive antennas. For systems with multiple receive antennas, we develop a diversity receiver for the wellseparated antennas. For systems with multiple transmit antennas, we propose to make use of Alamouti’s space-time transmission scheme, and develop the corresponding channel estimation and interference cancellation receiver techniques. Simulation results are provided to demonstrate the performance of various UWB receiver techniques developed in this paper.

• ETRI Journal
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• 제35권6호
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• pp.949-959
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• 2013

Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.