• 전자공학회논문지CI
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• 제46권4호
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• pp.69-78
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• 2009

DV-Hop 알고리즘에서 일반노드의 위치는 앵커노드 간 거리의 평균적인 값을 통해 계산되기 때문에 일반노드의 예측 위치와 실제 위치 간에 많은 오차가 존재한다. 본 논문에서는 앵커노드의 예측 위치와 실제 위치에서 발생하는 오차를 최소화하는 한 홉의 거리를 산출하고 그 거리를 이용하여 일반노드의 위치 정확도를 향상시키는 알고리즘을 제안한다. 또한 실제 거리에 비해 많은 홉 수를 지니는 앵커노드의 홉 당 거리로 인해서 발생하는 일반노드의 위치 오차를 보정하기 위해 일반노드는 앵커 노드들의 홉 당 거리를 평균으로 하는 자신만의 홉 당 평균 거리를 통해서 자신의 위치를 인식한다. 시뮬레이션을 통해서 제안하는 알고리즘이 기존의 DV-Hop보다 높은 위치인식 정확도를 보임을 확인한다.

• 한국정보통신학회논문지
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• 제25권11호
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• pp.1551-1558
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• 2021

실내 측위 시스템에 사용되는 Beacon의 신호는 반사 및 왜곡되어 노이즈 신호가 발생한다. 이 노이즈를 제거하기 위해 KF(Kalman Filter)가 널리 사용되어 왔다. KF를 적용하기 위해서는 각 제품의 신호 종류와 강도, 환경을 고려한 Parameters 최적화 과정이 필요하다. 본 논문에서는 BLE Beacon 기반 실내 측위 시스템에서 GA(Genetic Algorithm)를 활용한 KF Parameters의 최적화 문제 해결 방안을 제안한다. Beacon과 수신기 사이에 일정 거리를 두고 제안한 기법을 적용하여 KF Parameters를 최적화한 후, KF를 통과한 추정거리와 필터링을 거치지 않은 거리를 비교하였다. 제안하는 기법은 RSSI(Received Signal Strength Indi- cation)를 기반으로 하는 실내 측위 시스템에서 KF의 Parameters 최적화 소요시간 단축과 정확도 향상이 가능할 것으로 기대된다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.227-230
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• 2011

본 논문에서는 ALPS(Ad hoc network Localized Positioning System)알고리즘에 의해 위치 정보를 받아 새로운 헤드 노드를 에너지 효율성을 고려하여 선출하는 ECOPS(Energy Conserving optimal Path Schedule)알고리즘을 제안한다. 제안된 알고리즘은 계층적 클러스터 구조인 상황인식 기반의 RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol) 추론망 구조를 따르며, 노드의 위치 정보를 이용하여 에너지 효율적인 클러스터를 생성 및 유지하고, 전체 라우팅 구조의 라이프 타임을 증가시키는 방법이다.

• 한국해양공학회지
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• 제7권2호
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• pp.79-90
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• 1993

A design method of DPS control algorithm for adpting rotable thruster is introduced by applying servo system design method and the control algorithm is evaluated on the basis of the results of computer simulations performed for a semi-submersible 2-lower hull 8-column type platform. It is observed from the simulation results that position error due to the irregular drifting forces becomes zero after very short regulating time and dynamic positioning system is robust in spite of random disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.258-260
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• 2005

We describe a method for localizing a mobile robot in the working environment using a vision system and VRML. The robot identifies landmarks in the environment and carries out the self-positioning. The image-processing and neural network pattern matching technique are employed to recognize landmarks placed in a robot working environment. The robot self-positioning using vision system is based on the well-known localization algorithm. After self-positioning, 2D scene is overlaid with VRML scene. This paper describes how to realize the self-positioning and shows the result of overlaying between 2D scene and VRML scene. In addition we describe the advantage expected from overlapping both scenes.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2009년도 춘계학술대회 논문집
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• pp.239-244
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• 2009

This paper suggests a precision positioning control technique of a precision positioning stage with coupling effects. The precision positioning stage is supported by four flexible spring hinges and driven by two piezoelectric actuators. The dynamic characteristics of the precision positioning stage is modeled and identified by the FEM analysis. The dynamic characteristics of the stage are also identified by the frequency domain modeling technique based on the experimental data. Reliability of two modeling methods is examined by comparing the numerically and experimentally produced responses of the stage. This paper proposes a sliding mode control technique with integrator to improve the tracking ability of the precision positioning stage to the complex input signal using. To demonstrate the effectiveness of the proposed modeling schemes and control algorithm, experiment validations are performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권3호
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• pp.794-814
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• 2012

We propose a novel method for improving Wi-Fi positioning accuracy while reducing the energy consumption of mobile devices. Our method presents three contributions. First, we jointly and intelligently select the optimal subset of access points for positioning via maximum mutual information criterion. Second, we further propose local discriminant embedding algorithm for nonlinear discriminative feature extraction, a process that cannot be effectively handled by existing linear techniques. Third, to reduce complexity and make input signal space more compact, we incorporate clustering analysis to localize the positioning model. Experiments in realistic environments demonstrate that the proposed method can lower energy consumption while achieving higher accuracy compared with previous methods. The improvement can be attributed to the capability of our method to extract the most discriminative features for positioning as well as require smaller computation cost and shorter sensing time.

• IEIE Transactions on Smart Processing and Computing
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• 제2권4호
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• pp.208-215
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• 2013

Early iterations of the existing Global Positioning System (GPS)-based or radio lateration technique-based vehicle localization algorithms suffer from flip ambiguities, forged relative location information and location information exchange overhead, which affect the subsequent iterations. This, in turn, results in an erroneous neighbor-vehicle map. This paper proposes an extended information overlap measure (EIOM) algorithm to reduce the flip error rates by exchanging the neighbor-vehicle presence features in binary information. This algorithm shifts and associates three pieces of information in the Moore neighborhood format: 1) feature information of the neighboring vehicles from a vision-based environment sensor system; 2) cardinal locations of the neighboring vehicles in its Moore neighborhood; and 3) identification information (MAC/IP addresses). Simulations were conducted for multi-lane highway scenarios to compare the proposed algorithm with the existing algorithm. The results showed that the flip error rates were reduced by up to 50%.

• Journal of Positioning, Navigation, and Timing
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• 제13권3호
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• pp.277-287
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• 2024

In satellite systems, efficient communication and observation require identifying of specific signal arrival points using onboard antenna systems. When utilizing massive array antennas to estimate the angle of arrival (AOA) of signals, traditional high-performance AOA estimation algorithms such as Multiple Signal Classification (MUSIC) encounter extremely high complexity due to the numerous individual antenna elements. Although, in order to improve this computational complexity problem, the cascade AOA estimation algorithm with CAPON and beamspace-MUSIC was recently proposed, the comparison of the computational complexity of the proposed algorithm across different massive array antenna configurations has not yet been conducted. In this paper, we provide the analyzed results of the computational complexity of the proposed cascade algorithm based on various massive array antennas, and determine an optimal antenna configuration for the efficient AOA estimation in satellite systems.

• Journal of Astronomy and Space Sciences
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• 제28권3호
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• pp.217-223
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• 2011

Precise point positioning (PPP) is increasingly used in several parts such as monitoring of crustal movement and maintaining an international terrestrial reference frame using global positioning system (GPS) measurements. An accuracy of PPP data processing has been increased due to the use of the more precise satellite orbit/clock products. In this study we developed PPP algorithm that utilizes data collected by a GPS receiver. The measurement error modelling including the tropospheric error and the tidal model in data processing was considered to improve the positioning accuracy. The extended Kalman filter has been also employed to estimate the state parameters such as positioning information and float ambiguities. For the verification, we compared our results to other of International GNSS Service analysis center. As a result, the mean errors of the estimated position on the East-West, North-South and Up-Down direction for the five days were 0.9 cm, 0.32 cm, and 1.14 cm in 95% confidence level.