• 전기전자학회논문지
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• 제20권1호
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• pp.1-8
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• 2016

In this paper, we propose an effective time-of-arrival (TOA)-based localization method with adaptive bias computation in indoor environments. The goal of the localization is to estimate an accurate target's location in wireless localization system. However, in indoor environments, non-line-of-sight (NLOS) errors block the signal propagation between target device and base station. The NLOS errors have significant effects on ranging between two devices for wireless localization. In TOA-based localization, finding the target's location inside the overlapped area in the TOA-circles is difficult. We present an effective localization method using compensated distance with adaptive bias computation. The proposed method is possible for the target's location to estimate an accurate location in the overlapped area using the measured distances with subtracted adaptive bias. Through localization experiments in indoor environments, estimation error is reduced comparing to the conventional localization methods.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.17-24
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• 2016

In this paper, we introduce indoor localization technologies categorizing them into ON/OFF switch and senor based, wireless communication based, and image based technologies. Then we describe several representative techniques for each of them, emphasizing their strengths and weaknesses. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Our analyses show that ON/OFF switch based technologies are difficult to install, but accurate and not limited by light. Wireless communication technologies are not limited by light nor distance (space) and do not need additional device. Image based technologies do not need additional device but are limited by light, and their accuracies are affected by light. We believe that this paper provide wise view and necessary information for recent indoor localization technologies.

• ETRI Journal
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• 제41권6호
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• pp.739-749
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• 2019

Security and accuracy are two issues in the localization of wireless sensor networks (WSNs) that are difficult to balance in hostile indoor environments. Massive numbers of malicious positioning requests may cause the functional failure of an entire WSN. To eliminate the misjudgments caused by malicious nodes, we propose a compressive-sensing-based multiregional secure localization (CSMR_SL) algorithm to reduce the impact of malicious users on secure positioning by considering the resource-constrained nature of WSNs. In CSMR_SL, a multiregion offline mechanism is introduced to identify malicious nodes and a preprocessing procedure is adopted to weight and balance the contributions of anchor nodes. Simulation results show that CSMR_SL may significantly improve robustness against attacks and reduce the influence of indoor environments while maintaining sufficient accuracy levels.

• 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.

• 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.

• 한국통신학회논문지
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• 제41권6호
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• pp.640-651
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• 2016

본 논문은 실내 환경에서 정확도를 고려한 효과적인 도래시간 기반 무선 측위 방법을 제안하였다. 위치 측위의 목적은 타겟의 위치를 추정하는 것이다. 실내 환경에서 타겟의 정확한 위치를 추정하는 것은 다양한 오류들 때문에 어렵다. 무선 측위의 정확성은 비가시성 오류에 큰 영향을 받는다. 도래시간 기반 측위는 수신기와 3개 이상의 송신기 들 사이에서 거리 값을 이용하여 위치를 추정한다. 그러나 송신기와 수신기의 위치에 따라 장애물들로 인해 각각의 비가시성 오류도 다르다. 수신기의 위치를 정확하게 추정하기 위해서는 최적화된 위치 측위 방법이 필요하다. 본 논문은 무선 센서 네트워크에서 정확도를 높이기 위한 효과적인 측위 방법을 제안한다. 측위 시스템의 정밀도를 높이기 위해 거리 측정 단계에서의 거리 값을 보정하는 방법과 비가시성 환경에서 발생하는 오차들을 최소화시켜 효율적으로 송신기들을 선택하는 알고리즘을 제안하여 성능을 향상시켰다. 제안한 방법의 성능 평가는 다양한 오차들이 존재하는 실제 환경에서의 실험들로 인해 제시되었고, 실험적인 결과들은 기존의 방법과 제안된 방법을 가진 측위 절차의 추정 오차 결과들의 비교를 통해 측위 시스템의 정확도가 향상된 것을 증명하였다.

• 한국컴퓨터정보학회논문지
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• 제21권6호
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• pp.55-62
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• 2016

In this paper, we present indoor positioning technologies using the wireless signal categorizing them into triangulation based, fingerprinting based, and cell ID based technologies. We describe several representative techniques for each of them emphasizing their strengths and weaknesses. We define important performance issues for indoor positioning technologies and analyze recent technologies according to the performance issues. We believe that this paper provide wise view and necessary information for recent indoor positioning technologies using wireless signals.

• Journal of Advanced Marine Engineering and Technology
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• 제39권2호
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• pp.187-194
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• 2015

Accurate relative location estimation is a key requirement in indoor localization systems based on wireless sensor networks (WSNs). However, although these systems have applied not only various optimization algorithms but also fusion with sensors to achieve high accuracy in position determination, they are difficult to provide accurate relative azimuth and locations to users because of cumulative errors in inertial sensors with time and the influence of external magnetic fields. This paper based on ultra-wideband positioning system, which is relatively suitable for indoor localization compared to other wireless communications, presents an indoor localization system for estimating relative azimuth and location of location-unaware nodes, referred to as target nodes without applying any algorithms with complex variable and constraints to achieve high accuracy. In the proposed method, the target nodes comprising three mobile nodes estimate the relative distance and azimuth from two reference nodes that can be installed by users. In addition, in the process of estimating the relative localization information acquired from the reference nodes, positioning errors are minimized through a novel modified rounding estimation technique in which Kalman filter is applied without any time consumption algorithms. Experimental results show the feasibility and validity of the proposed system.

• 공학교육연구
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• 제13권5호
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• pp.76-80
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• 2010

In this paper, the Location Compensation Mechanism using equivalent distance rate ($LCM_{edr}$) for localization system based on SDS-TWR (Symmetric Double-Sided Two-Way Ranging) in wireless sensor network is proposed. The performance of the mechanism is experimented in terms of two types of the localization tracking scenarios of indoor and outdoor environments in university campus. From the experimentations, the compensation ratio in the $LCM_{edr}$ is better than that in SDS-TWR about 90% in indoor/outdoor environments in scenario 1 but also is better than that of SDS-TWR about 91.7% in indoor environment and about 100% in outdoor environment in scenario 2 respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.