• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.918-931
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• 2013

The conventional object tracking techniques using PTZ camera detects object movements by analyzing acquired image. However, this technique requires expensive hardware devices to perform a complex image processing. And it is occasionally hard to detect object movements, if an acquired image is low quality or image acquisition is impossible. In this paper, we proposes a smart security CCTV system applying to wireless sensor network technique based on IEEE 802.15.4 standard to overcome the problems of conventional object tracking technique, which enables to track suspicious objects by detecting object movements and GPS data in sensor node. This system enables an efficient control of PTZ camera to observe a wide area, decreasing image processing complexity. Also, wireless sensor network is implemented using mesh networks to increase the efficiency of installing sensor node.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.51-64
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• 2009

A location tracking sensor such as GPS, INS, Radar, and optical equipments is used in tracking Maneuvering Targets with a multi-sensor, and such systems are used to track, detect, and control UAV, guided missile, and spaceship. Until now, Most of the studies related to tracking Maneuvering Targets are on fusing multiple Radars, or adding a supplementary sensor to INS and GPS. However, A study is required to change the degree of application in fusions since the system property and error property are different from sensors. In this paper, we perform the error analysis of the sensor properties by adding a ground radar to GPS and INS for improving the tracking performance by multi-sensor fusion, and suggest the tracking algorithm that improves the precision and stability by changing the sensor probability of each sensor according to the error. For evaluation, we extract the altitude values in a simulation for the trajectory of UAV and apply the suggested algorithm to carry out the performance analysis. In this study, we change the weight of the evaluated values according to the degree of error between the navigation information of each sensor to improve the precision of navigation information, and made it possible to have a strong tracking which is not affected by external purposed environmental change and disturbance.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.18-22
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• 2012

This paper suggests an altitude determination algorithm using GPS and barometric altitude sensors and evaluates the algorithm by digital map contour. A code based GPS altitude has lots of errors so that the car navigation companies can not use this data. Therefore, altitude is calculated by convergence data with GPS and barometric altitude variance in this paper. The modified altitudes are compared with the digital map contour and then this algorithm's effect is evaluated for the car navigation systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.545-548
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• 2018

본 논문에서는 모바일 디바이스의 GPS, Compass, Gyroscope Sensor를 이용하여 실외 공간의 위치를 찾아주는 실시간 AR 나침반을 제안한다. 제안 AR 나침반에서는 모바일 디바이스의 Sensor 이용하여 사용자의 위치와 방향, 실외 공간의 위치와 방향을 계산하여 안내 Object의 크기와 가시화 여부를 결정하고 보여줌으로 사용자가 실외 공간의 위치를 찾아갈 수 있도록 하는 나침반을 설계 구현하였다.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.417-425
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• 2012

It is well known that GPS cannot provide positioning results if sufficient number of visible satellites are not available. To overcome this weak point, attentions have been recently moved to hybrid positioning methods that augments GPS with other sensors. As an extension of hybrid positiong methods, this paper proposes a new method that combines GPS and vision sensor to improve availability and accuracy of land vehicle positioning. The proposed method does not require any external map information and can provide position solutions if more than 2 navigation satellites are visible. To evaluate the performance of the proposed method, an experiment result with real measurements is provided and a result shows that accumulated error of n-axis is almost 2.5meters and that of e-axis is almost 3meters in test section.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.293-294
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• 2011

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.800-808
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• 2008

This paper presents a localization algorithm of the outdoor wheeled mobile robot using the sensor fusion method based on indirect Kalman filter(IKF). The wheeled mobile robot considered with in this paper is approximated to the two wheeled mobile robot. The mobile robot has the IMU and encoder sensor for inertia positioning system and GPS. Because the IMU and encoder sensor have bias errors, divergence of the estimated position from the measured data can occur when the mobile robot moves for a long time. Because of many natural and artificial conditions (i.e. atmosphere or GPS body itself), GPS has the maximum error about $10{\sim}20m$ when the mobile robot moves for a short time. Thus, the fusion algorithm of IMU, encoder sensor and GPS is needed. For the sensor fusion algorithm, we use IKF that estimates the errors of the position of the mobile robot. IKF proposed in this paper can be used other autonomous agents (i.e. UAV, UGV) because IKF in this paper use the position errors of the mobile robot. We can show the stability of the proposed sensor fusion method, using the fact that the covariance of error state of the IKF is bounded. To evaluate the performance of proposed algorithm, simulation and experimental results of IKF for the position(x-axis position, y-axis position, and yaw angle) of the outdoor wheeled mobile robot are presented.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.65-71
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• 2023

In this paper, we design and implement the Walking Life Festival application, which is based on the Android platform and provides information about domestic travel destinations and regional festivals in South Korea. This application utilizes various sensors found in smartphones, including the Step Counter sensor, Step Detector sensor, Acceleration sensor, and GPS sensor. Additionally, it makes use of Google Map API and Public Open API to offer information about domestic travel destinations and local festivals. The application also incorporates an automatic login feature using the Shared Preference API. When storing login information in the database, it encrypts the input plaintext data using a hash algorithm. For Google Maps integration, it creates objects using the Google.maps.LatLngBounds() method and extends the location information through the extends method. Furthermore, this application contributes to the activation of the domestic tourism industry by notifying users about the timing of local festivals related to domestic travel destinations, thus increasing their opportunities to participate in these festivals.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.35-43
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• 2004

Multibeam Echosounder system is the latest technology of a hydrographic survey utilized in producing an electronic nautical chart, obtaining a DEM with high precision, making a moving image by Swath surveying a wide area. As a fundamental study for improving the precision of MBES, we compared and analyzed measurements of DGPS and Motion sensor, and studied for the dynamic characteristics of vessel's movements. DGPS was installed in front and in the rear and on both side or the vessel and surveyed. The receiving precision of surveyed GPS results was obtained to the satisfactory extent that was possible to valuate the accuracy of Motion sensor as 0.0016$^{\circ}$ of the roll value and 0.0009$^{\circ}$ of the pitch value. The relationship between the values of heading, pitch, and roll in Motion sensor and the data of DGPS was proportional correlation. In addition, it is considered that deviations by elements like rapid turning and vibration of the vessel will be occurred, although the correlation of each deviation according to each amount or change is proportional. It is suitable that GPS installs in the central line of the vessel that is less affected than other places by waving because the amount of change in the tide level obtained from GPS survey and the value of heave are similar with the values taken by Motion sensor, and the velocity of GPS is different from installed places. The accuracy of the final result from MBES could be affected by the values of gyro and Motion sensor inputted to MBES processor because there were intervals of 15s and 13s of receiving time in gyro and Motion sensor respectively compared with the real-time measurements of DGPS.