• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2195-2202
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• 2011

Recently, navigation system is used to inform users of vehicle location and driving direction, moving distance and so on. This navigation uses GPS sensor for current location determination. The GPS sensor will determinate current coordinates by using triangulation algorithm. This characteristic bring about that the GPS signal is not available in the shadow region such as tunnel and urban canyon. Moreover, Even though the signal is available, inherent positional error rate of the GPS often results in the dislocation of vehicle. To solve, these problems, a new positioning system is proposed in the paper. The System utilizes geomagnetic sensors of smartphone, speed information of CAN of vehicle though bluetooth and WiFi APs for GPS shadow area. The experimental test shadows that the proposed system using multiple data is able to determine the position of vehicle in GPS shadow areas.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.534-543
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• 2008

To use the Global Positioning System (GPS) carrier phase measurement for precise positioning, the integer ambiguities at the early stage of most algorithms must be determined. Furthermore, if a precise positioning is to be applied to real time navigation, fast determination and validation methods for integer ambiguity are essential. In this paper, the Wald test that simultaneously determines and validates integer ambiguities is used with assistance of the Inertial Navigation System (INS) to improve its performance. As the Wald test proceeds, it assigns a higher probability to the candidate that is considered to be true at each time step. The INS information is added during the Wald test process. Large performance improvements were achieved in convergence time as well as in requiring fewer observable GPS satellites. To test the performance improvement of the Wald test with the INS information, experimental tests were conducted using a ground vehicle. The vehicle moved in a prescribed trajectory and observed seven GPS satellites. To verify the effect of the INS information on the Wald test, the convergence times were compared with cases that considered the INS information and cases that did not consider the INS information. The results show that the benefits of using the INS were emphasized as fewer GPS satellites were observable. The performance improvement obtained by the proposed algorithm was shown through the fast convergence to the true hypothesis when using the INS measurements.

• The KIPS Transactions:PartC
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• v.15C no.1
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• pp.31-36
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• 2008

The clock frequency difference of sensor nodes is one of main parameters in TOF estimation and affect to degrade ranging algorithms to estimate positions of mobile nodes in wireless sensor networks. The specification of IEEE802.15.4a describes asynchronous TWR and SDS-TWR insensitive to frequency difference without any additional network synchronization. But the TWR and SDS-TWR can not eliminate sufficiently the effect of frequency difference of node pair, packet processing delay and its difference. Especially use of low cost oscillator with wide range offset, sensor node with different hardware and software can make the positioning errors worse. We propose an estimation method of frequency differences, and apply the measured frequency differences to TWR and SDS-TWR. We evaluate the performance of the proposed algorithm with simulation, and make certain that the proposed method enhances the performance of existing algorithms with positioning errors less than 25 cm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1003-1006
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• 2009

Recently, Ubiquitous computing technology is increasing necessity for object recognition and a location tracking technology to meet various applications. The location tracking technology is the fundamental to the Context-Aware of users in Ubiquitous environment and its efficiency has to be improved using IEEE 802.15.4 ZigBee used in current infra such as ubiquitous sensor network. But because the IEEE 802.15.4 ZigBee protocol has limitation to apply location tracking technology such as ToA and TDoA, Zone-based Location Tracking technology using RSSI is needed. In this paper suggests RSSI-based 802.15.4 ZigBee local positioning protocol to support a positioning tracking service in Ubiqutous environment. And Zone-based location tracking system is designed for actual the indoor location tracking service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.156-170
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• 2019

Rapid increasing of smartphones has changed people's lifestyles, and location-based services are providing a platform to provide various conveniences in accordance with these changes. In particular, it may provide convenience to many users if location-based services are provided in an indoor area such as subway station. However, it is still a difficult task to ensure accurate positioning result for guiding routes in subway stations. This study proposes a KAI-R system that allows all processes to be performed in one system for indoor navigation in subway stations. The proposed system includes a new pedestrian step detection method for continuous positioning along with an improved fusion positioning algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1280-1287
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• 2020

This paper proposes a vision-based food recognition method for automated production of custom cakes. A small camera module mounted on a food art printer recognizes objects' shape and estimates their center points through image processing. Through the perspective transformation, the top-view image is obtained from the original image taken at an oblique position. The line and circular hough transformations are applied to recognize square and circular shapes respectively. In addition, the center of gravity of each figure are accurately detected in units of pixels. The test results show that the shape recognition rate is more than 98.75% under 180 ~ 250 lux of light and the positioning error rate is less than 0.87% under 50 ~ 120 lux. These values sufficiently meet the needs of the corresponding market. In addition, the processing delay is also less than 0.5 seconds per frame, so the proposed algorithm is suitable for commercial purpose.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.13-20
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• 2021

A series of numerical experiments with measurements observed at continuously operating reference stations (CORS) of the international GNSS services (IGS) and the national geographical information institute of Korea (NGII) have been intensively carried out to evaluate the quality of pseudo-ranges and carrier-phases of GPS L2C signal obtained by various receiver types, benign and harsh operational environment. In this analysis, some quality measures, such as signal-to-noise ratio (SNR), the magnitude of multipath, and the number of cycle slips, the pseudo-range and carrier phase obtaining rate were computed and compared. The SNR analysis revealed an impressive result that the trend in the SNR of C/A and the L2C comparably depends upon type of receivers. The result of multipath analysis also showed clearly different tendency depending on the receiver types. The reason for this inconsistent tendency was seemed to be that the different multipath mitigation algorithm built-in each receiver. The number of L2C cycle slip was less than P2(Y), and L2C measurements obtaining rate was higher than that of P2(Y) in three receiver types. In the harsh observational environment, L2C quality was not only superior to P2(Y) in all aspects such as SNR, multipath magnitude, the number of cycle slips, and measurement obtaining rate, but also it could maintain a level of quality equivalent to C/A. According to the results of this analysis, it's expected that improved positioning performance like accuracy and continuity can be got through the use of L2C instead of existing P2(Y).

• Journal of the Korean Society for Precision Engineering
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• v.24 no.3 s.192
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• pp.67-75
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• 2007

This paper deals with a problem of vibration suppression of a piezoelectric beam using a self-sensing algorithm. Two methods, which are PPF(positive position feedback) and SRF(strain rate feedback), are considered to suppress a residual vibration of a piezoelectric beam developed during the step positioning of a beam end point. A self-sensing algorithm treated here is basically a strain rate estimator of a beam movement and is to be used for the closed loop control. The efficacy of the proposed idea is evaluated through experiments.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.565-570
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• 2015

Supervised machine learning has become popular in discovering context descriptions from sensor data. However, collecting a large amount of labeled training data in order to guarantee good performance requires a great deal of expense and time. For this reason, semi-supervised learning has recently been developed due to its superior performance despite using only a small number of labeled data. In the existing semi-supervised learning algorithms, unlabeled data are used to build a graph Laplacian in order to represent an intrinsic data geometry. In this paper, we represent the unlabeled data as the spatial-temporal dataset by considering smoothly moving objects over time and space. The developed algorithm is evaluated for position estimation of a smartphone-based robot. In comparison with other state-of-art semi-supervised learning, our algorithm performs more accurate location estimates.