• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.359-364
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• 2003

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.249-255
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• 2002

Since the stationary alignment process of the SDINS is not completely observable, some furls of the aided alignment have been applied. The purpose of this paper is to propose a new initial alignment algorithm, which utilizes the attitude output from the AGPS(Attitude Determination GPS) receiver and to demonstrate the feasibility of the proposed algorithm with several experimental results. A Kalman filter is designed for utilizing the attitude output as well as the zero velocity information. Also analyzed is the observability of the SDINS error model. To show the feasibility of the proposed scheme, we implement an alignment system where HG1700AE IMU (Inertial Measurement Unit) from Honeywell and an AGPS receiver designed at Chungnam National University are used. Test trials are done to evaluate the performance of the proposed alignment scheme. The proposed algorithm provides as good initial alignment performance as a high accurate navigation system, MAPS(Modular Azimuth Positioning System) INS.

• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.351-366
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• 2002

In this study, we developed low cost INS and (D)GPS integration for continuous attitude and position and utilized it for the determination of exterior orientation parameters of image sensors which are equipped in 4S-Van. During initial alignment process, the heading information was extracted from twin GPS and fine alignment with Kalman filter was performed for the determination of roll and pitch. Simulation and van test were performed for the performance analysis. Based on simulation result, roll and pitch error is around 0.01-0.03 degrees and yaw error around 0.1 degrees. Based on van test, position error in linear road is around 10 cm and curve around 1 m. Using direct georeferencing method, the image sensor's orientation and position information can be acquired directly from (D)GPS/INS integration. 4S-Van achieved 3D spatial data using (D)GPS/INS and image data can be applied to the spatial data integration and application such as contemporary digital map update, road facility management and Video GIS DB.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.59-64
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.377-382
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• 2003

차량측량시스템이란 차량에 2대 이상의 CCD 카메라와 위치측정장비(GPS, IMU 등)를 장치하고 도로를 운행하면서 일정한 간격으로 주변의 사진을 연속으로 촬영한 후 이를 이용하여 도로 및 도로시설물의 위치와 크기, 보존상태 등의 정보를 취득하는 새로운 측량 시스템이다. 본 연구에서는 대상물의 3차원 위치결정을 위해 필요한 자료와 자료를 처리하는 각 단계를 체계화하였으며, 사용 편의성과 위치결정정확성을 높일 수 있는 차량측량시스템을 위한 수치사진측량 프로그램을 개발하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.145-150
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• 2003

Mobile mapping system is a surveying system that use vehicle carrying various sensors as CCD camera, GPS and IMU(Inertial measurement Unit). This system capturing images of forward direction continuously while running road. Use these images, then acquire road and road facilities information as facilities position, size or maintenance condition. In this study, we organized data and each data processing steps that are needed for 3 dimensional positioning. And develop digital photogrammetry S/W easy to use and accurate for mobile mapping system.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.2
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• pp.97-107
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• 2016

Military Autonomous Underwater Vehicle (AUV) is utilized to search a mine under the sea. This paper presents design and performance verification of real-time hybrid navigation system for AUV. The navigation system uses Doppler Velocity Log (DVL) integration method to correct INS error in underwater. When the AUV is floated on the water, the accumulated error of navigation algorithm is corrected using position/velocity of GPS. The navigation algorithm is verified using 6 Degree Of Freedom (DOF) simulation, Program In the Loop Simulation (PILS). Finally, the experiments are performed in real sea environment to prove the reliability of real-time hybrid navigation algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.373-379
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• 2015

A hybrid navigation system is implemented to apply for a mobile robot. The hybrid navigation system consists of an inertial navigation system and a global positioning system. The inertial navigation system quickly calculates the position and the attitude of the robot by integrating directional accelerations, angular speed, and heading angle from a strap-down inertial measurement unit, but the results are available for a short time since it tends to diverge quickly. Global positioning system delivers position, heading angle, and traveling speed stably, but it has large deviation with slow update. Therefore, a hybrid navigation system uses the result from an inertial navigation system and corrects the result with the help of the global positioning system where an indirect feedback Kalman filter is used. We implement and confirm the performance of the hybrid navigation system through driving a car attaching it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5219-5226
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• 2014

This paper proposes an improved scheme of pedestrian position information system using neural network theory in a GPS-disabled area. Through a learning/obtaining gait pattern and step distance about walk, run, duck walk, crab walk and crawl, the position estimation error could be minimized by rejecting the inertial navigation drift. A portable hardware module was implemented to evaluate the performance of the proposed system. The performance and effectiveness of the suggested algorithm was verified by experiments indoors.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.18-24
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• 2015

Train positioning detection information is fundamental for high-speed railroad inspection, making it possible to simultaneously determine the status and evaluate the integrity of railroad equipment. This paper presents the results of measurements and an analysis of an inertial measurement unit (IMU) used as a positioning detection sensors. Acceleration and angular rate measurements from the IMU were analyzed in the amplitude and frequency domains, with a discussion on vibration and train motions. Using these results and GPS information, the positioning detection of a Korean tilting train express was performed from Naju station to Illo station on the Honam-line. The results of a synchronized analysis of sensor measurements and train motion can help in the design of a train location detection system and improve the positioning detection performance.