• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1337-1362
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• 2020

Advances in localization-based technologies and the increase in ubiquitous computing have led to a growing interest in location-based applications and services. High accuracy of the position of a wireless device is still a crucial requirement to be satisfied. Firstly, the rapid development of wireless communication technologies has affected the location accuracy of radio monitoring systems employed locally and globally. Secondly, the location is determined using standard complex computing methods and needs a relatively long execution time. In this paper, two geolocalization techniques, based on trigonometric and CORDIC computing processes, are proposed and implemented for Bluetooth-based indoor monitoring applications. Theoretical analysis and simulation results are investigated in terms of accuracy, scalability, and responsiveness. They show that the proposed techniques can locate a target wireless device accurately and are well suited for timing estimation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1360-1362
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• 1999

This paper describes the fault location technique using wavelets in transmisson line. Estimation of fault location is performed using synchronized data sampled at two ends of line and travelling wave. The similar current wave modeled in PSCAD/EMTDC and MATLAB was applied to evaluate the accuracy of theory proposed in this paper. The results of fault location shown in this paper will be evaluated as an effective suggestion for fault location in real transmisson line

• 인터넷정보학회논문지
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• 제2권5호
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• pp.49-58
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• 2001

Mobile positioning measurement is the most important technology for Location Based Services in the cellular networks. Generally, we are expecting to use GPS to guarantee high accuracy of the mobile position, A CDMA network-based technique for the Mobile Station position calculation needs to be implemented in the cdma2000 network whether the handsets have GPS or not, The most reliable methods of the network-based location technologies are based on the estimation of time of signal traveling between MS and B18 in a network whose coordinates are identified, Other signal parameters such as the power of the received signal and the signal arrival direction cannot be used as main data for a location system because adoption of only the signal parameters will not meet the FCC requirements, In practice, the estimates of the time of signal propagation between MS and BTS always have errors resulting from low-resolution power of measurements and multi path signal propagation, This paper describes the combined network-based location technology in the cdma2000 1× necessary to meet US FCC requirements. The issues of a calibration table and statistic processing based on the pilot strength as well as combined network-based location technologies(TOA/ TDOA) will help to achieve higher location accuracy than specified in the US FCC Rule.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.308-311
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• 2008

WSN(Wireless Sensor Network)의 기술 요소 중의 하나는 센서노드의 위치에 관한 정보를 추적하고 관리하는 것으로 GPS, 초음파, RSSI 등을 이용하는 방법이 대표적이다. 본고에서는 RSSI에 기반의 무선 센서 노드 위치 측정 방법의 정확도를 향상시키기 위하여 사하기 위하여 무선센서노드의 위치를 판정하기 위하여 전파수신강도(RSSI)의 측정값의 정확도를 향상하기 위하여 을 회귀분석을 이용하는 방법에 대해 고찰하였다. 또한 Friis 공식을 이용 송신기와 수신기 사이에서의 전파의 경로 손실과 한 위치 측정하는 기존의 방식과 RSSI 값에 기반하여 회귀분석을 이용한 위치 측정 방식을 비교 분석한 결과 회귀분석을 이용한 방식이 RSSI를 이용하여 거리를 측정하는 측면에서 좀 더 향상된 정확도를 나타내었다.

• 한국컴퓨터정보학회논문지
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• 제26권6호
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• pp.29-35
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• 2021

본 논문에서는 위치 측위의 정확도를 높일 수 있는 방안으로 KNN(K-Nearest Neighbor)과 Local Map Classification 및 Bayes Filter를 융합한 기법을 제안한다. 먼저 이 기법은 Local Map Classification이 실제 지도를 여러 개의 Cluster로 나누고, 다음으로 KNN으로 Cluster들을 분류한다. 그리고 Bayes Filter가 획득한 각 Cluster의 확률을 통하여 Posterior Probability을 계산한다. 이 Posterior Probability으로 로봇이 위치한 Cluster를 검색한다. 성능 평가를 위하여 KNN과 Local Map Classification 및 Bayes Filter을 적용하여서 얻은 위치 측위의 결과를 분석하였다. 분석 결과로 RSSI 신호가 변하더라도 위치 정보는 한 Cluster에 고정되면서 위치 측위의 정확도가 높아진다는 사실을 확인하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.286-288
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• 2003

In this paper, we present our implementation of the direct camera model (image to ground) for SPOT5 and use it to assess the geometric accuracy of SPOT5 imagery. Our assessment confirms the location accuracy of SPOT5 imagery (without use of GCPs) is less than 50m. We further introduce a few attitude parameters to refine the camera model with GCPs. The model is applied to two SPOT5 supermode images, one near vertical, incidence angle of 3 degrees, and one far oblique, incidence angle of 27 degrees. The results show that accuracy (rms of check points) of about one pixel (2.5m) can be achieved with about 4 GCPs by using only 3 parameters to correct the yaw, pitch and roll of the satellite.

• 제어로봇시스템학회논문지
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• 제17권1호
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• pp.47-53
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• 2011

To enable the efficient operation of ITS, it is necessary to collect location data for vehicles on the road. In the case of futuristic transportation systems like ubiquitous transportation and smart highway, a method of data collection that is advanced enough to incorporate road lane recognition is required. To meet this requirement, technology based on radio frequency identification (RFID) has been researched. However, RFID may fail to yield accurate location information during high-speed driving because of the time required for communication between the tag and the reader. Moreover, installing tags across all roads necessarily incurs an enormous cost. One cost-saving alternative currently being researched is to utilize GNSS (global navigation satellite system) carrierbased location information where available. For lane recognition using GNSS, a precise digital map for determining vehicle position by lane is needed in addition to the carrier-based GNSS location data. A "precise digital map" is a map containing the location information of each road lane to enable lane recognition. At present, precise digital maps are being created for lane recognition experiments by measuring the lanes in the test area. However, such work is being carried out through comparison with vehicle driving information, without definitions being established for detailed performance specifications. Therefore, this study analyzes the performance requirements of a precise digital map capable of lane recognition based on the accuracy of GNSS location information and the accuracy of the precise digital map. To analyze the performance of the precise digital map, simulations are carried out. The results show that to have high performance of this system, we need under 0.5m accuracy of the precise digital map.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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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.

• 대한안전경영과학회지
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• 제14권1호
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• pp.217-224
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• 2012

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.335-345
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• 2017

Recently, location systems using RFID technology have been studied in indoor environments. However, the existing techniques require high computational cost to compute the location of a moving object because they compare the location proximity of all reference tags and objects. In this paper, we propose an RFID based location positioning scheme using event filtering, which reduces the computation cost of calculating the locations of moving objects while maintaining the accuracy of location estimation. In addition, we propose an incremental location update policy to reduce the location update cost for moving objects. We also compare the proposed scheme with one of the localization schemes, LANDMARC using a performance evaluation. As a result, the proposed scheme outperforms LANDMARC in terms of the computational cost of location estimation. The proposed scheme also reduces the cost of location update by using the RFID-based update policy.