• ETRI Journal
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• 제34권5호
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• pp.684-689
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• 2012

A mode-singular-value-decomposition (SVD) maximum likelihood (ML) estimation procedure is proposed for the source localization problem under an additive measurement error model. In a practical situation, the noise variance is usually unknown. In this paper, we propose an algorithm that does not require the noise covariance matrix as a priori knowledge. In the proposed method, the weight is derived by the inverse of the noise magnitude square in the ML criterion. The performance of the proposed method outperforms that of the existing methods and approximates the Taylor-series ML and Cram$\acute{e}$r-Rao lower bound.

• Journal of information and communication convergence engineering
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• 제8권6호
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.501-504
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• 2002

This research embodied DGPS (Differential GPS) system that robot detects users present position in outside environment as part of Lacteal gland robot that is sight obstacle. Therefore, introduced GPS system that is effective means that can save essential world coordinate to realize global navigation. However, it is no the effectiveness to use GPS that is having error of tens meter to apply to lacteal gland robot that is sight obstacle without revision. Therefore, this research embodied Localization system of lacteal gland robot that is sight obstacle using DGPS that make use of FM DARC system to use DGPS to heighten navigation accuracy of this.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.639-647
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• 2020

In the vibration target localization algorithms based on time difference of arrival (TDOA), Fang algorithm is often used in practice because of its simple calculation. However, when the delay estimation error is large, the localization equation of Fang algorithm has no solution. In order to solve this problem, one dimensional search location algorithm based on TDOA is proposed in this paper. The concept of search is introduced in the algorithm. The distance d1 between any single sensor and the vibration target is considered as a search variable. The vibration target location is searched by changing the value of d1 in the two-dimensional plane. The experiment results show that the proposed algorithm is superior to traditional methods in localization accuracy.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.837-840
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• 2010

Wireless Sensor Networks have been proposed for several location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point to point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we proposed a Coefficient Allocated DV-Hop (CA DV-Hop) algorithm which reduces node's location error by awarding a credit value with respect to number of hops of each anchor to an unknown node. Simulation results have verified the high estimation accuracy with our approach which outperforms the classical DV-Hop.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• 한국항행학회논문지
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• 제15권1호
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• pp.83-90
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• 2011

위치인식 기술은 사물이나 사람의 위치를 측정하여 서로 정보를 교환하고 환경을 제어하는데 필요한 핵심기술이다. 현재도 위치인식 기술은 다양한 방법들로 연구되고 있으며, 물류, 의학, 로봇 분야 등에 적용될 수 있다. 그러나 위치인식 기술을 적용하려면 많은 비용이 필요하다. 이에 본 논문에서는 적은 비용으로 구현 가능한 Zigbee기반 AoA 위치인식 시스템을 제안한다. 본 시스템은 흔히 이용하는 스텝 모터, 지향성 안테나, Zigbee 모듈을 사용하여 비컨에 지향성 안테나를 회전시켜 RSSI값을 측정하였다. RSSI값이 가장 큰 값을 가질 때 스텝 모터의 회전각을 계산하여 수신기가 위치한 각도를 판단하고 AoA 방식을 적용하여 수신기의 위치를 측정하였다. 수신기의 위치를 옮겨가며 측정한 결과 35~36cm 정도의 오차가 있었다.

• 한국정보통신학회논문지
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• 제20권3호
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• pp.499-505
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• 2016

본 논문에서는 웨어러블 컴퓨터 시스템을 위한 WUSB over WBAN 프로토콜에서 요구되는 신체 영역 위치인식기술을 제안한다. 제안하는 위치인식기술은 웨어러블 컴퓨터의 주변 장치를 구성하는 WUSB over WBAN 프로토콜 기반 센서노드에서 실행된다. 웨어러블 컴퓨터 시스템에서 다양한 신체 모션을 통한 입력 정보의 정확성을 높이기위해서는, 높은 정밀도를 갖는 새로운 위치인식기술이 반드시 개발되어야 한다. 이러한 목적을 달성하기 위해, 본 논문은 신체에 부착된 WUSB over WBAN 디바이스들의 개수를 4개 이상으로 하는 TDoA/FDoA/AoA 복합 방식을 제안한다. 실험 결과에서는 제안하는 TDoA/FDoA/AoA의 복합 방식 알고리즘이 TDoA/FDoA 복합 알고리즘 보다 위치 추정 오차를 10mm 감소시킨다. 이 값은 다른 통신 시스템에서는 무시할 수 있는 작은 값이나, 신체 영역 내 통신에서는 위치 추정 성능을 향상시키는 결과를 나타낸다.

• 한국전자통신학회논문지
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• 제6권2호
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• pp.288-295
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• 2011

본 논문에서는 몬테 카를로 방법을 사용한 수중로봇의 위치추정 방법을 제안한다. 수중로봇의 위치추정은 자율 주행을 위한 기본 기능의 하나이다. 제안된 알고리즘에 의하면 추측항법(데드 레크닝 방법)의 약점인 위치 오차 누적 문제를 해결할 수 있다. 제안된 방법은 확률적인 방법으로 로봇 동작의 불확실성과 센서 정보의 불확실성을 처리한다. 특히 칼만 필터 방법과 달리, 로봇의 비선형 운동 특성과 센서의 비가우시안 출력 분포 특성을 모델링할 수 있다. 본 논문에서는 수중로봇 위치 추정에 몬테카를로 위치추정(Monte Carlo Localization : MCL, 이하 MCL로 표기함) 알고리즘을 적용하기 위하여 오일러각을 이용하여 모션모델을 구하였다. 또한 수중로봇에 모션모델과 센서모델을 적용하여 시뮬레이션을 구현하고, 이를 통해 수중로봇에 MCL 알고리즘의 적용 가능성을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.