• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.552-557
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• 2015

Recent performed by recognizing a user's location, various services have been tailored focus on short-range wireless communication technology. A beacon in which is attracting attention as next-generation technology. Beacon is a terminal by utilizing the frequency of the non-audible area can not be bluetooth and human sending and receiving terminals and information, Apple recently iBeacon like a low-power Bluetooth (BLE; bluetooth low energy) based beacon showing a tendency to rise into the mainstream there. Services using a beacon is basically installs the terminal in a certain place indoor. It is characterized by providing the user the services to catch the user's position, even automatically take a separate action. Various types of location-based service provided by the target interior space began to attract attention. A variety of location-based services are provided in the interior space in order to be successfully deployed and provide guidance to the interior space, the movement route and the like are essentially required to build various types of information. In this paper, for efficient indoor positioning by varying the signal strength of the beacon in such areas were measured and analyzed.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.220-226
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• 2013

Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.605-612
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• 2008

This paper researches the estimating location using repeater effect adjustment method in CDMA based system. Repeaters are commonly used by commercial and amateur radio operators to extend signals in the radio frequency range from one receiver to another. The repeater signals are increasing arrival time from base station to mobile station. So if we calculates the mobile station using repeater signals, the estimating position error is increased. However nobody researched about adjusting repeater effects. This paper proposes repeater effect adjustment algorithm. For adjusting repeater effects, we make the triangle using mobile station, reference base station and neighbor base station, and then detect the repeater effects using the triangle characteristic. The proposed method system showed the improved performance in estimating parameters and locating positions by computer simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.25-31
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• 2017

The indoor location based service proposed in the study was assigned to target a moving user. Positioning in the outdoor environment is accurate while using GPS. However, in an indoor environment, positioning is inaccurate and difficult. In order to overcome this, studies of various techniques for positioning based on wireless communication such as Wi-Fi, Zigbee and Bluetooth are being performed. The RSSI value and the delivery signal of the bluetooth beacon are measured according to the distance, and to a database. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance. When average and feedback filtering coefficient are set with 0.5, irregular and highly RSSI values are decreased. As the distance increases, the range of error is confirmed to have a reduction when using a distance calculation correction algorithm. Finally, when using the RSSI measurement results filtering, it corrects an unstable signal. Also, the distance correction algorithm is used to reduce a range of errors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.75-76
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• 2022

WPS is a system that finds the location of a current moving object through information of a wireless AP. The current location is determined by utilizing the outdoor and indoor AP signal strength characteristics. Even if the map is configured for the first service, the map information of the DB built by the variability of the AP signal cannot be 100% reliable in the case of outdoor. Therefore, various algorithms are needed to increase the accuracy of WPS. This paper proposes a system to increase positioning accuracy by applying various methods to determine the current position of a moving object.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.361-365
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• 2007

위치정보는 유비쿼터스 컴퓨팅의 가장 중요한 항목 중 하나이다. 일반적인 위치 인식 시스템은 GPS가 대표적이지만, 실내에서 사용할 수 없고 건물내부와 같은 좁은 지역에서의 위치 인식이 어렵다는 단점이 있다. 특히 핸드폰, PDA와 같은 개인용 장비 에서는 더욱 정교한 위치 인식 기술이 필요한데, 무선랜을 기반으로 하는 위치 인식 기술은 그러한 목적을 달성하기에 적절하다. AP (Access Point)로부터 수집된 무선 신호의 세기는 모바일 기기의 위치를 측정하는데 필요한 지도로써 사용할 수 있지만, 건물의 벽, 사물, 사람 등과 같은 장애물의 간섭으로 변화가 심해 쉽게 사용할 수 없다. 본 논문에서는 이러한 문제점을 극복하기 위하여 신경망 모델을 이용한 무선랜 환경에서의 위치 인식 시스템을 제안한다. 아울러 신경망 학습에 사용될 학습데이터의 오차를 보정하고, 중복을 제거하기 위하여 칼만 필터를 사용하였다.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2012.06a
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• pp.135-135
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• 2012

USN(Ubiquitous Sensor Network)을 이용한 실내 위치 인식 기술은 주요한 연구 분야이며 산업에 미치는 영향이 매우 크다. 좁은 복도 환경에서는 삼변측위를 이용하지 않고 이변측위만 이용하더라도 Mobile Node의 위치 측정이 가능하다. 하지만 이변측위를 이용할 경우 Reference Node 사이의 간격이 멀어 질수록 Mobile Node의 위치 정보 수신율이 떨어져 Mobile Node의 위치를 표시할 수 없게 된다. 따라서 본 연구에서는 관성센서 및 초음파 센서를 이용하여 위치 정보의 수신이 이루어지지 않는 상황에서도 Mobile Node의 위치를 표시할 수 있게 구성하고 실험을 통하여 검증하였다.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.117-123
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• 2012

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system using the active RFID is developed to satisfy such a demand based on the results of previous research. First of all the design considerations and functions of the system are introduced. In sequence the functions of the system is presented, and then the performance of the developed system is tested and verified through various field tests. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.262-264
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• 2013

본 논문은 실내에서 사용자의 위치를 측위하기 위해 건물 실내에 설치되어 있는 Wireless AP(Access Point)에서 발신되는 RSSI(Received signal strength indication)를 수집한 후 Friis 공식을 통해 거리로 변환하여 위치를 측위한다. Friis 공식을 적용하는 과정에서 RSSI 신호가 약할수록 거리의 오차가 매우 심하게 변동되기 때문에 본 논문에서는 이러한 오차를 개선하기 위해 신호세기가 강한 2개의 AP좌표와 RSSI를 이용하여 두 원의 교점을 구하는 방정식과 좌표 사이의 거리를 구하는 방정식을 사용하는 위치측위 시스템을 구현하였고, 실험결과 제안한 방법이 기존의 삼각측량법보다 오차가 개선되었음을 확인할 수 있었다.