• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3534-3553
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• 2021

The low cost of Bluetooth technology has led to its wide usage in indoor positioning. However, some inherent shortcomings of Bluetooth technology have limited its further development in indoor positioning, such as the unstable positioning state caused by the fluctuation of Received Signal Strength Indicator (RSSI) and the low transmission frequency accompanied by a poor real-time performance in positioning and tracking moving targets. To address these problems, an indoor fusion positioning algorithm of Bluetooth technology and pedestrian dead reckoning (PDR) based on a particle filter with dynamic adjustment of weights calculation strategy (BPDW) will be proposed. First, an orderly statistical filter (OSF) sorts the RSSI values of a period and then eliminates outliers to obtain relatively stable RSSI values. Next, the Group-based Trilateration algorithm (GTP) enhances positioning accuracy. Finally, the particle filter algorithm with dynamic adjustment of weight calculation strategy fuses the results of Bluetooth positing and PDR to improve the performance of positioning moving targets. To evaluate the performance of BPDW, we compared BPDW with other representative indoor positioning algorithms, including fingerprint positioning, trilateral positioning (TP), multilateral positioning (MP), Kalman filter, and strong tracking filter. The results showed that BPDW has the best positioning performance on static and moving targets in simulation and actual scenes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.50-55
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• 2023

Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• 전기전자학회논문지
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• 제26권2호
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• pp.186-195
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques using Wi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, a popular method widely used for indoor positioning, however, it improves some disadvantages of the Weighted Centroid method and also for other kinds of indoor positioning methods, by using the received signal strength correction method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is caused by the complex propagation environment. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several access points around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracy positioning system, which can be used in any building environment with an available Wi-Fi access point setup as a beacon node.

• 한국정보통신학회논문지
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• 제27권1호
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• pp.139-142
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• 2023

In this paper, we propose a GNSS-UWB hybrid positioning system for indoor and outdoor seamless positioning. Fusion of GNSS and inertial sensors has been widely used as a method for estimating positions in places where GNSS reception sensitivity is low, and UWB technology, which started as a short-range wireless communication technology, is widely used indoors where GNSS is completely blocked. This paper proposes a method of mutual correction and fusion of the location information collected through GNSS and the location information collected from the UWB indoor positioning system when indoor and outdoor work occurs continuously and repeatedly, such as in an industrial site.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.213-214
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• 2023

Positioning information of workers is important for safety management at construction sites. Among the various indoor positioning technologies, geomagnetic fields-based technology is more economical and has less error than other technologies. However, there is a problem that the installation and dismantling of materials such as formwork at construction sites can cause degradation in positioning performance. Therefore, in this study, the distortion of the geomagnetic field near euro-form was quantitatively measured and the application method of geomagnetic field-based indoor positioning technology on formwork stage was presented. The results showed that the distortion occurred within 10cm of the wall and column form, but positioning accuracy could be affected up to 60cm from the form due to the characteristic of geomagnetic field-collecting technology. Therefore, applying this technology to the formwork stage requires complementary measures, such as using other positioning techniques up to 60 cm near the formwork, or excluding distorted area when positioning. It is expected that this study can contribute to the efficient safety management of workers by suggesting ways to prevent an increase in positioning error when applying geomagnetic field sequence-based indoor positioning technology during the formwork stage.

• 한국인터넷방송통신학회논문지
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• 제16권2호
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• pp.123-129
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• 2016

스마트폰에서 음향 신호를 이용하여 실내에서의 절대 위치를 측정하는 연구가 많이 진행되고 있다. 또한 여러개의 위치 측정 장치들이 연속으로 자신의 위치를 측정하는 멀티 홉 방식의 실내 위치 측정 장치 시스템도 제안되었다. 이 경우에는 측정된 상대 위치의 오차가 축적되어 홉 수가 커짐에 따라 지속적으로 증가하게 되므로 실내 위치 측정 시스템을 설계할 때에 이에 대한 분석이 필요하다. 본 논문에서는 연속적으로 설치된 멀티 홉 방식의 실내 위치 측정 장치 시스템에서 절대 위치 오차를 분석하였으며, 이를 시뮬레이션을 통해 검증하였다. 분석 결과를 보면 축적된 측정 오차가 멀티 홉 수에 따라 거의 선형적으로 증가함을 확인할 수 있다.

• 한국통신학회논문지
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• 제38C권1호
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• pp.131-140
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• 2013

기존의 전파에 의존한 실내 위치측위 시스템의 한계점 발생으로 실내환경에서 정확도 향상을 위한 새로운 방법의 도입이 필요한 시점이다. 최근 생태계 모방 기술이 미래의 핵심기술이 되었고, 이에 따라 귀소본능을 가진 동물들이 지구자기장을 탐색하여 생체자석으로 위치친지에 사용하는 점을 적용한 정확한 위치 측위 방법을 연구하였다. 실내 위치측위를 위한 새로운 자원인 지구자기장의 적용 가능성을 확인하기 위해 건물구조, 구성재료를 구분하고 실제 자기장센서를 탑재할 수 있는 구조물과 데이터수집 모듈을 설계한 뒤, Fingerprint 기법의 위치측위 시스템을 구성하여 위치측위 자원으로서의 지구자기장의 적용 가능성을 연구하였다. 위치측위 시스템 성능 평가에서 기존의 무선랜이 설치된 건물에서는 지구자기장 세기 기반의 위치측위 시스템이 무선랜 기반 위치측위 시스템과 유사하거나 약 20% 성능이 높이 나타났다. 이와같이 실내 위치측위를 위한 인프라 설치가 되어 있지 않는 환경에서는 지구자기장이라는 고유의 지구자원으로 실내 위치측위가 가능하다.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.146-151
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• 2013

With the development of mobile internet, requirements of positioning accuracy for the LBS (Location Based Service) are becoming more and more higher. The LBS is based on the position of each mobile device. So, it requires a proper acquisition of accurate user's indoor position. Thus indoor positioning technology and its accuracy is crucial for various LBS. In general, RSSI (Received Signal Strength Indicator) measurements are used to obtain the position information of mobile unit under WLAN environment. However, indoor positioning error increases as multiple AP's configurations are becoming more complex. To overcome this problem, an enhanced indoor localization method by AP (Access Point) selection criteria adopting DOP (Dilution of Precision) is proposed.