• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.192-197
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• 2020

Recently, the technologies related to autonomous drive has studying the goal for safe operation and prevent accidents of vehicles. There is radar and camera technologies has used to detect obstacles in these autonomous vehicle research. Now a day, the method for using LiDAR sensor has considering to detect nearby objects and accurately measure the separation distance in the autonomous navigation. It is calculates the distance by recognizing the time differences between the reflected beams and it allows precise distance measurements. But it also has the disadvantage that the recognition rate of object in the atmospheric environment can be reduced. In this paper, point cloud data by triangular functions and Line Regression model are used to implement measurement algorithm, that has improved detecting objects in real time and reduce the error of measuring separation distances based on improved reliability of raw data from LiDAR sensor. It has verified that the range of object detection errors can be improved by using the Python imaging library.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.97-107
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• 1999

Passive sensors such as Laser Range Finder(LRF) and Forward Looking Infrared(FLIR) camera frequently used for tracking aircraft landing produce the measurements of elevation angle contaminated by large noise due to the exhaust plume disturbance. This results in poor tracking performance if the extended Kalman filter is used for estimation of the range and elevation which are corrupted by the non-Gaussian noise such as plume disturbance. In this paper, an adaptive estimation filter and the extended Kalman filter is combined to produce a combination-type filter. In this approach the adaptive filter is used for the plume-type disturbance noise and the extended Kalman filter is utilized for the measurement of Gaussian type. The proposed combination filter is effective for the trajectory estimation of landing aircraft under the influence of unknown bias and numerical simulations illustrate the performance of the proposed filter.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.361-368
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• 2015

This paper reports an unscented Kalman filter approach for localization of a mobile robot in an indoor environment. The method proposes a new model of measurement uncertainty which adjusts the error covariance according to the measured distance. The method also uses non-zero off diagonal values in error covariance matrices of motion uncertainty and measurement uncertainty. The method is tested through experiments in an indoor environment of 100*40 m working space using a differential drive robot which uses Laser range finder as an exteroceptive sensor. The results compare the localization performance of the proposed method with the conventional method which doesn't use adaptive measurement uncertainty model. Also, the experiment verifies the improvement due to non-zero off diagonal elements in covariance matrices. This paper contributes to implementing and evaluating a practical UKF approach for mobile robot localization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.131-138
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• 2023

In this paper, a free space optical communication device that can be used in a mobile base station of several km or less was fabricated and its characteristics were investigated. To overcome the loss due to atmospheric transmission, an optical fiber amplifier (EDFA) with an output of 23 dBm or more was used. In order to increase the focusing speed and miniaturization of the laser beam, an optical lens was manufactured, and a transmission lens was designed to have beam divergence within the range of 1.5 to 1.8 [mrad]. A PT module that controls PAN/TILT was fabricated in order to reduce pointing errors and effective automatic alignment between transceiver devices. In this study, Reed-Solomon (RS) code was used to maintain the transmission quality above a certain level. It was manufactured to be able to communicate at a wireless distance of 300m in a weather situation with visibility of 300m. For performance measurement, it was measured using BERT and eye pattern analyzer, and it was confirmed that BER can be maintained at 2.5Gbps.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.145-157
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• 2017

Currently, the height of ships that can pass under Busan Harbor Bridge is limited to 60m or shorter, so that large-sized ships of 60m or taller cannot use Busan Harbor international passenger terminal. Accordingly, this study has developed a service which measures continuously the change of bridge height by water level changes and provides such in real-time for safe bridge passage of large-sized ships of 60m or taller. The measurement system comprised of high-precision laser distance measurement device, GPS sensor, optical module, and damping structure is used to measure the bridge height change according to tide level changes, and the measured information is provided in real-time through cloud-based mobile app. Also, in order to secure objective bridge height data for changes to height limits and navigation supports, the observation data was analyzed and forecast model was drawn. As a result, it became an objective evidence to revise the passage height rules of the Busan Port Bridge from 60 meters to 63 meters.