• Journal of Communications and Networks
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• 제7권3호
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• pp.284-293
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• 2005

A critical issue in applications involving networks of wireless sensors is their ability to synchronize, and mitigate the fading propagation channel effects. Especially when distributed 'slave' sensors (nodes) reach-back to communicate with the 'master' sensor (gateway), low power cooperative schemes are well motivated. Viewing each node as an antenna element in a multi-input multi-output (MIMO) multi-antenna system, we design pilot patterns to estimate the multiple carrier frequency offsets (CFO), and the multiple channels corresponding to each node-gateway link. Our novel pilot scheme consists of non-zero pilot symbols along with zeros, which separate nodes in a time division multiple access (TDMA) fashion, and lead to low complexity schemes because CFO and channel estimators per node are decoupled. The resulting training algorithm is not only suitable for wireless sensor networks, but also for synchronization and channel estimation of single- and multi-carrier MIMO systems. We investigate the performance of our estimators analytically, and with simulations.

• IEIE Transactions on Smart Processing and Computing
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• 제6권3호
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• pp.175-182
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• 2017

In this paper, we present a multi-depth generation method using a time-of-flight (ToF) fusion camera system. Multi-view color cameras in the parallel type and ToF depth sensors are used for 3D scene capturing. Although each ToF depth sensor can measure the depth information of the scene in real-time, it has several problems to overcome. Therefore, after we capture low-resolution depth images by ToF depth sensors, we perform a post-processing to solve the problems. Then, the depth information of the depth sensor is warped to color image positions and used as initial disparity values. In addition, the warped depth data is used to generate a depth-discontinuity map for efficient stereo matching. By applying the stereo matching using belief propagation with the depth-discontinuity map and the initial disparity information, we have obtained more accurate and stable multi-view disparity maps in reduced time.

• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.23.3-23
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• 2001

The main object of this work is the development of an intelligent multi-sensor integration and fusion model that uses fuzzy inference system. Sensor data from different types of sensors are integrated and fused together based on the confidence which is not typically used in traditional data fusion methods. The information is fed as input to a fuzzy inference system(FIS). The output of the FIS is weights that are assigned to the different sensor data reflecting the confidence En the sensor´s behavior and performance. We interpret a type of fuzzy inference system as an interpolator of B-spline hypersurfaces. B-spline basis functions of different orders are regarded as a class of membership functions. This paper presents a model that ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.91.4-91
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• 2001

In this paper, a development of the sensor fusion algorithm for a visual control of mobile robot is presented. The output data from the visual sensor include a time-lag due to the image processing computation. The sampling rate of the visual sensor is considerably low so that it should be used with other sensors to control fast motion. The main purpose of this paper is to develop a method which constitutes a sensor fusion system to give the optimal state estimates. The proposed sensor fusion system combines the visual sensor and inertial sensor using a modified Kalman filter. A kind of multi-rate Kalman filter which treats the slow sampling rate ...

• 정보통신설비학회논문지
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• 제8권3호
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• pp.116-121
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• 2009

A novel method for improving the reliability of sensing data using multi-sensors in wireless sensor network systems is presented in this paper. This method is successfully applied a fog monitoring system in the mountain area.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.149-156
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• 2011

This paper reveals a distance estimation algorithm based on multi-code ultrasonic and wireless sensor network. For measuring the distances among the sensor nodes, each ultrasonic transmitter transmits multi-code ultrasonic signal simultaneously. Receivers use cross correlation method to separate the coded signals. The information of measured distances is broadcasted to each sensor node by wireless sensor network. The wireless sensor network measures the distance among the sensor nodes using the received signal strength of the broadcasting. The multi-code ultrasonic have a limitation of measurable distance. And the received signal strength is affected from an environment. This paper measures a distance using ultrasonic and a received signal strength in short range. These measured data are applied to the least square estimation algorithm. By the expansion of the fitting curve, a distance measurement in long range using the received signal strength is compensated. The coupled system reduce the error to an acceptable level.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 춘계종합학술대회
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• pp.472-475
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• 2005

본 논문에서는 다중센스 환경에서 센스정보를 Kalman-Fuzzy 시스템을 이용하여 정보를 통합하고 정확하게 프로세스의 상태를 예측하는 시스템을 제안한다. 제안한 방식은 Kalman 필터를 이용하여 보다 신뢰할 수 있는 센스정보를 획득하고, 다중센스로부터 정보를 퍼지 시스템을 이용하여 통합할 수 있다. 제안한 방식의 유용성을 확인하기 위하여 Electro-Hydraulic 엑추에이트를 대상으로 위치 추적을 시뮬레이션 하였고 제안한방식의 우수한 성능을 확인하였다.

• 한국정보통신학회논문지
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• 제25권7호
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• pp.977-985
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• 2021

자율주행 차량이 주목받게 되면서 LiDAR 센서가 대두되었다. LiDAR 센서는 LASER를 이용하여 범위 내에서 특정 지점까지 측정된 거리 값을 3차원 정보로 제공한다. 3차원 거리 값인 만큼 방대한 데이터를 전송하게 되고, 차량의 메인 프로세서 등에서 다른 데이터와 같이 이를 실시간으로 처리하기에는 무리가 있다. 이러한 이슈를 해결하기 위해 통합처리 시스템을 개발하고자 한다. 시스템은 센서로부터 데이터를 받아 처리하는 client와 각 client로부터 데이터를 취합하여 이를 외부로 전송하는 server 프로세스로 구성된다. 각 프로세스의 데이터 수신 및 처리 방법, 프로세스 구동 방법을 변화시켜가며 시스템의 실시간성 확보를 위한 테스트를 진행하였다. 실험 결과, 4대의 LiDAR 센서로 데이터를 수신 받도록 하였으며, background 나 multi-core processing을 적용하여 프로세스를 동작시켰을 때, 각 client는 약 13.2 ms, server는 약 12.6 ms의 응답시간을 확인할 수 있었다.

• 한국정밀공학회지
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• 제14권11호
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.