• ETRI Journal
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• v.26 no.5
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• pp.497-500
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• 2004

In this paper, we present a novel idea to integrate a low cost inertial measurement unit (IMU) and Global Positioning System (GPS) for land vehicle localization. By taking advantage of positioning data calculated from an image based on photogrammetry and stereo-vision techniques, errors caused by a GPS outage for land vehicle localization were significantly reduced in the proposed bimodal approach. More specifically, positioning data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate for IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method, which can be used to reduce positioning errors caused by a low cost IMU when a GPS signal is not available in urban areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.11-21
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• 2000

The travel behavior should be analysed microscopically for the traffic management of urban street. The car following theory which found out the correlation between the lead and the following vehicles is being widely used as basic data in many fields. As the vehicle position and its speed information can be received by GPS, this technique is recently applying to the various fields. For the case study the travel data were collected with two vehicles equipped with GPS receiver. The moving distance was calculated by the collected location data every 2 seconds and the speed variation was checked. And this study analysed and compared the acceleration and deceleration speed between the lead and the following vehicle. Finally, Regression model about the relationship between the acceleration and deceleration speed and the acceleration and deceleration distance was constructed. This model could be helpful for the road design and the regulation for the safe traffic management.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.13-21
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• 2004

GPS is widely used in various applications since GPS receivers are capable of measuring precise position and velocity in any weather condition for a relatively low cost. However, GPS requires more than four simultaneously visible GPS satellites for optimal performance. In high-motion, high-attitude-changing applications, there exist some situations where less than four satellites are visible or where the dilution of precision (DOP) is high. In this paper, we propose a simulation algorithm that predicts the performance of GPS navigation according to changes in vehicle attitude. We have compared simulation results with experimental results, where simulation results of the proposed algorithm are shown to closely match actual experimental data. This algorithm could be used to predict GPS navigational performance and to determine optimal GPS antenna position.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.2
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• pp.171-176
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• 2007

The tracking antenna must always point to track moving vehicle for data link. In this paper, we determine pointing angle from the geometric relationship of antenna and UAV(Unmaned Aerial Vehicle) to let an antenna be toward a moving vehicle. The pointing angle of antenna is set through GPS measurement data installed in antenna and UAV. We verify the performance of this system from the fixing a camcoder on the antenna.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.53.3-53
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• 2002

1. Introdition : The necessity of DGPS data compensation. 2. Configuration of the GPS and coordinates conversion 2-1. Coordinates conversion of CCD 3. Vehicle Model and Evaluation 4. Accurate error position algorithm. 5. Experiment and result. 6. Conclusion: It was possible that we converted the CCD data into the GPS coordinates data.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.55-63
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• 2010

This paper describes performance improvement of GPS/DR Integration system using area decision algorithm and vehicle movement information. In GPS signal blockage area, i.e., tunnel and underground parking area, DR sensor errors are accumulated and navigation solution is gradually diverged. We use the car movement information according to moving area to correct the DR sensor error. Also, vehicle movement is decided as stop, straight line, turn and movement changing region through DR sensor data analysis. The car experiment is performed to verify the supposed method. The results show that supposed method provides small position and heading error than previous method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.2
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• pp.15-24
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• 2016

GPS(Global Positioning System) location tracking is a method for taking the precise coordinates after the coordinates are obtained by a GPS receiver, and displaying them on the map. In this paper with WAVE(Wireless Access for Vehicular Environment) simulation, we show that various services such as vehicle tracking service, real-time road conditions service and logistics can go tracking service, control and operation services according to the vehicle position and the traveling direction by using the GPS position data. A vehicle tracking system using GPS is automatically able to manage multiple RCP when exchanging data between RMA and the RCP, and it provides rapid requests and responses. To verify that multiple sessions between RMA and RM, as well as multiple sessions between RMA and RCP are able to be implemented, we take RMA as a RCP application on an OBU, until the RMA is receiving data response from corresponding RM. As a result of this experiment, we show that the response speeds of single session between RMA and RM using 1, 2, 3, and 4 kbyte unit data are similar, 62.32ms, 62.65ms, 63.02ms, and 63.48ms, respectively. Likewise, those of 128 muliple sessions using 1, 2, 3, and 4 kbyte unit data are not much more time difference, 298.08ms, 302.21ms, 322.85ms, and 329.62ms, respectively.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.443-447
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• 1996

The meeds of vehicle navigation system are increassing and the accurate determination of position is still of promary improtance. GPS (Global Positioning System)receiver and low cost dead reckoning sensors have been used for vehicle position location. The integartion of these can improve the system performance to cope with accumulating errors and multipath problem in urban area. However, the implementation of integrated system of two sensors is net easy, for their real data ave noises that are not apt to be modeled. This paper discusses how to combine a GPS receiver and dead reckoning sensors. The characteriatics of sensors and their data are investigated, and the system for field test is manufactured. The test results of a selected typical route are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.64.5-64
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• 2001

It is a very important problem that we grasp the accurate position at car navigation system. The GPS has used for knowing position because of accumulating few errors, but it have errors that are Tropospheric error, ionospheric error and Multipath error and so on. In this paper, We estimate moving position of a vehicle by Kalman filter using initial value after deducing the line equation using initial value and target value of map data. Then, we compensate GPS errors compare estimated poing with GPS errors. The experimental results have shown that are compared position data during real travel with compensated position data which are got after applying the algorithm ...