• 한국전자통신학회논문지
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• 제8권3호
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• pp.465-470
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• 2013

Dempster-Shafe 증거이론은 다중센서 데이터융합을 위한 좋은 계산방법을 제공해준다. 이때 기본확률배정 함수가 절대적으로 필요하다. 본 논문에서는 신호를 평가하여 기본확률배정함수를 계산하고 결정하는 방법을 제안한다. 센서들이 보내온 신호를 구간별로 변화율을 평가하고 이 평가를 기초로 기본확률배정함수를 정하도록 한다. 센서들이 감지하여 보고한 신호들은 상황발생 요인과 관련 있는데, 시간간격에 따라서 변화하는 신호값의 추이를 평가하였다. 센서가 감지한 신호의 변화는 상황구성 및 병화와 밀접한 관련이 있으므로 신호값의 변화를 평가하는 것은 상황추론에 도움이 되는 것이었다. 이것을 기본확률배정함수 결정에 포함함으로써 사전정보가 없는 경우에 대해서도 상황추론이 가능할 수 있음을 보였다.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.156-161
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• 2003

An overview of our approach to autonomous navigation is presented showing how motion information can be integrated into existing navigation schemes. Particular attention is given to our short range motion estimation scheme which utilises a number of unique assumptions regarding the nature of the visual environment allowing a direct fusion of visual and range information. Graduated non-convexity is used to solve the resulting non-convex minimisation problem. Experimental results show the advantages of our fusion technique.

• 한국통신학회논문지
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• 제42권3호
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• pp.604-611
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• 2017

무선 센서 네트워크에서 센서 노드는 제한된 전력을 사용하기 때문에 에너지 사용을 효율적으로 하는 것이 중요하다. 본 논문에서는 에너지사용효율을 높이기 위해 일정지역에서 측정되는 센서 값으로 이루어진 행렬이 low rank일 때 Matrix Completion을 이용하여 패킷 생성량을 줄이고, 센서가 측정값에 대응시킨 time slot으로 센서 ID 전송을 시도할 때 확률밀도함수로 예측한 전송 성공 확률에 따라 전송을 결정하여 overhead와 충돌을 줄이는 방법을 제안한다. 전산 모의실험을 통해 CSMA/CA와 비교하여 제안된 방법이 전송 실패 수가 17% 감소하고 패킷 생성량은 73%로 감소함을 보였다. 또한 CSMA/CA에 비해 시간 지연이 22%로 감소하고 fusion center에서 Singular Value Thresholding(SVT)로 센서 값을 복원한 경우 MSE error가 CSMA/CA에 비해 86%로 낮음을 보였다.

• 센서학회지
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• 제28권4호
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.104.2-104
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• 2002

This paper proposes a sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable accurate measurement, such as, distance to an obstacle and location of the service robot itself. In the conventional fusion schemes, the measurement is dependent on the current data sets. As the results, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system , the temporal sequence of the data sets are stored and utilized for the measurement improvement. Theoretical basis is il lustrated by examples and...

• 대한전기학회논문지:시스템및제어부문D
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• 제55권9호
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• pp.401-408
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• 2006

In a multi-sensor multi-target tracking systems, the local sensors have the role of tracking the target and transferring the measurements to the fusion center. The measurements from the same target can arrive out of sequence called the out-of-sequence measurements(OOSMs). Out-of-sequence measurements can arise at the fusion center due to communication delay and varying preprocessing time for different sensor platforms. In general, the track fusion occurs to enhance the tracking performance of the sensors using the measurements from the sensors at the fusion center. The target informations can wive at the fusion center with the clutter informations in cluttered environment. In this paper, the OOSM update step with MPDA(Most Probable Data Association) is introduced and tested in several cases with the various clutter density through the Monte Carlo simulation. The performance of the MPDA with OOSM update step is compared with the existing NN, PDA, and PDA-AI for the air target tracking in cluttered and out-of-sequence measurement environment. Simulation results show that MPDA with the OOSM has compatible root mean square errors with out-of-sequence PDA-AI filter and the MPDA is sufficient to be used in out-of-sequence environment.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.909-914
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• 2007

In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window. The main purpose of this paper is to prevent a damage or crack from the fatigue in advance. 16 channel sensors data are considered and maximum stress is computed by a sensor fusion method every moving window. After the maximum stress every window is compared with a given threshold, this overload detecting algorithm decides overload or not.

• 한국분말재료학회지
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• 제24권5호
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• pp.351-356
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• 2017

Tin dioxide nanoparticles are prepared using a newly developed synthesis method of plasma-assisted electrolysis. A high voltage is applied to the tin metal plate to apply a high pressure and temperature to the synthesized oxide layer on the metal surface, producing nanoparticles in a low concentration of sulfuric acid. The particle size, morphology, and size distribution is controlled by the concentration of electrolytes and frequency of the power supply. The as-prepared powder of tin dioxide nanoparticles is used to fabricate a gas sensor to investigate the potential application. The particle-based gas sensor exhibits a short response and recovery time. There is sensitivity to the reduction gas for the gas flowing at rates of 50, 250, and 500 ppm of $H_2S$ gas.