• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1363-1370
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• 2018

In visible light (VL) positioning based on angle of arrival (AOA) estimation for smart indoor service, the AOA parameters obtained at the receiver has sometimes a random and distributed angle form instead of a point angle form due to the multipath transfer of the actual visible light and short positioning distance. The AOA estimation of a VL signal with a random and parametric distributed angle form may give incorrect AOA parameter estimates, which may result in poor VL positioning performance. In this paper, we classify the AOA parameters of the received VL signal into three forms according to the actual positioning channel environment and consider the short-range VL positioning method. We propose a subspace-based AOA parameter estimation technique and a data fusion method, and analyzed the proposed method by simulation and the measurement of the real VL channel characteristics.

• ETRI Journal
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• 제26권3호
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• pp.218-228
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• 2004

Using stereo images with ephemeris data from the Korea Multi-Purpose Satellite-1 electro-optical camera (KOMPSAT-1 EOC), we performed geometric modeling for three-dimensional (3-D) positioning and evaluated its accuracy. In the geometric modeling procedures, we used ephemeris data included in the image header file to calculate the orbital parameters, sensor attitudes, and satellite position. An inconsistency between the time information of the ephemeris data and that of the center of the image frame was found, which caused a significant offset in satellite position. This time inconsistency was successfully adjusted. We modeled the actual satellite positions of the left and right images using only two ground control points and then achieved 3-D positioning using the KOMPSAT-1 EOC stereo images. The results show that the positioning accuracy was about 12-17 m root mean square error (RMSE) when 6.6 m resolution EOC stereo images were used along with the ephemeris data and only two ground control points (GCPs). If more accurate ephemeris data are provided in the near future, then a more accurate 3-D positioning will also be realized using only the EOC stereo images with ephemeris data and without the need for any GCPs.

• Journal of Positioning, Navigation, and Timing
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• 제6권2호
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• pp.79-86
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• 2017

Precise Point Positioning-Real Time Kinematic (PPP-RTK) refers to a technology that combines PPP with network-RTK in which a user does not directly receive observed data from a reference station but receives State-Space Representation (SSR) messages corrected for error components from a central processing station through Networked Transport of RTCM via Internet Protocol (NTRIP) or Digital Multimedia Broadcasting (DMB) for purposes of positioning. SSR messages, which refer to corrections used in PPP-RTK, are generated by a central processing station using real-time observed data collected from reference stations and account for corrections needed due to the ionosphere, troposphere, satellite orbital errors, satellite time offsets, and satellite biases. This study used a type of SSR message provided in South Korea, known as Korea-SSR (K-SSR), to implement a PPP-RTK algorithm based on code-pseudorange measurements and validated its accuracy within the reference station network. In order to validate the accuracy of the implemented algorithm outside of the network, the K-SSR was extrapolated and applied to positioning in reference stations in Changchun, China (CHAN) and Japan (AIRA). This also entailed a quantitative evaluation that measured improvements in accuracy in comparison with point positioning. The results of the study showed that positioning applied with extrapolated K-SSR correction data was more accurate in both AIRA and CHAN than point positioning with improvements of approximately 20~50%.

• 전자공학회논문지S
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• 제34S권1호
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• pp.16-25
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• 1997

This paper shows the development of the high accuracy vehicle positioning algorithm using the differential technique in vehicle tracking systems form the existing vehicle position which is acquired from the global positioning system (GPS). The control center receives the satellite ephemerise data and pseudorange correction from the reference station, and vehicle position from the moving vehicle. The pseudorange is calculated with the satellite position and the vehicle position, and corrected by pseudorange correction. Using this corrected pseudorange and kalman filter, more improved vehicle positioning data were obtained.

• 로봇학회논문지
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• 제8권2호
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• pp.129-135
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• 2013

In this paper, a high precision outdoor positioning system is newly proposed using multiple GPS receivers based on the Extended Kalman Filter (EKF). Typically, the GPS signal has the instantaneous errors that degrade the positioning seriously. Using the multiple GPS receivers instead of an expensive DGPS receiver, the positioning reliability and accuracy are improved in this research as a low cost solution. To incorporate the small displacement, an INS data have been tightly coupled to the GPS data, which has the inherit disadvantage of the cumulative error occurring over time. To achieve a stabilized and accurate positioning system, the multiple GPS receiver data are fused with the INS data through the EKF process. Through real navigation experiments of an outdoor mobile robot, the performance of the proposed system has been verified to be accurate comparable to DGPS system with a lower cost.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2382-2386
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• 2003

The Global Positioning System(GPS) is a satellite based precise positioning system avaliable worldwide. The GPS have many error sources. The earth's ionosphere and atmosphere cause delays in the GPS signal that translate into position errors. Some errors can be factored out using mathematics and modeling. The configuration of the satellites in the sky can magnify other errors. The problem of accuracy on GPS measurement data can be meaningful. In this study, we propose the method for GPS positioning accuracy improvement. The FUZZY set theory on PDOP(Position Dilution of Precision) and SNR(Signal to Noise Ratio) provide improved for measured positioning data. The accuracy of positioning has been improved by selecting data from original using the FUZZY set theory on PDOP and SNR.

• Journal of Advanced Marine Engineering and Technology
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• 제24권1호
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• pp.119-126
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• 2000

In constructing the positioning system based on a conventional dead-reckoning for a wheeled vehicle with pneumatic tires, the position estimation error is inevitable as changes of the radius of the wheels depend on live load and variable enviroment. Therefore, this paper proposes the positioning system which can estimate the error source i.e. the vehicle parameter errors, such as the right and left wheel radius error, using gyroscope and ultrasonic sensor and correct the parameter to reduce the dead-reckoned position estimation error. The extended Kalman filter was used as a method for the multisensor data fusion. The simulation to verify the effectiveness of the proposed positioning system is performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• 한국측량학회지
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• 제31권6_2호
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• pp.539-547
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• 2013

This research is suggesting the most effective positioning method for GPS based positioning when no GPS reference point is available in the neighborhood. For this purpose, we carried out positioning of the IGS realtime observatories in Australia in various conditions. According to the research, we were certainly assured the one reference point with a short baseline length is more effective for differential positioning than multiple reference points with a long baseline distance beyond 1,000km and suggested the precise point positioning based positioning method can be an excellent substitute when no reference point is available around an unknown point. The research result may be used as the basic data for accurate positioning in poor reference point environments, especially in Antarctica.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.459-465
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• 2008

Locations of nodes as well as gathered data from nodes are very important because generally multiple nodes are deployed randomly and data are gathered in wireless sensor network. Since the nodes composing wireless sensor network are low cost and low performance devices, it is very difficult to add specially designed devices for positioning into the nodes. Therefore in wireless sensor network, technology positioning nodes precisely using low cost is very important and valuable. This research proposes Cooperative Positioning System, which raises accuracy of location positioning and also can find positions on multiple sensors within limited times.