• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.927-934
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• 2012

In this paper, we present relative positioning algorithm for moving land vehicle using GPS, MEMS IMU and B-CDMA module. This algorithm does not calculate precise absolute position but calculates relative position directly, so additional infrastructure and I2V communication device are not required. Proposed algorithm has several steps. Firstly, unbiased relative position is calculated using pseudorange difference between two vehicles. Simultaneously, the algorithm estimates position of each vehicle using GPS/INS integration. Secondly, proposed algorithm performs filtering and finally estimates relative position and relative velocity. Using proposed algorithm, we can obtain more precise relative position for moving land vehicles with short time interval as IMU sensor has. The simulation is performed to evaluate this algorithm and the several field tests are performed with real time program and miniature vehicles for verifying performance of proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2641-2647
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• 2003

Conventional DLLs estimate the delay times of satellite signals individually and feed back these measurements to the VCO independently. But VDLL estimates delay times and user position directly and then estimate the feedback term for VCO using the estimated position changes. In this process, input measurements are treated as vectors and these vectors are used for navigation. First advantage of VDLL is that noise is reduced in all of the tracking channels making them less likely to enter the nonlinear region and fall below threshold. Second is that VDLL can operate successfully when the conventional independent parallel DLL approach fails completely. It means that VDLL receiver can get enough total signal power to track successfully to obtain accurate position estimates under the same conditions where the signal strength from each individual satellite is so low or week that none of the individual scalar DLL can remain in lock when operating independently. To operate VDLL successfully, it needs to know the initial user dynamics and position and prevents total system from the divergence. The suggested integration method is to use the inertial navigation system to provide initial dynamics for VDLL and to maintain total system stable. We designed the GPS/INS integrated navigation system. This new type of integrated system contained the vector pseudorange format generation block, VDLL signal processing block, position estimation block and the conversion block from position change to delay time feedback term aided by INS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.359-366
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• 2005

Airborne LiDAR integrated with on-board GPS/INS and scanning technology is a state-of the-art system for direct 3D geo-spatial data acquisition. In this study, LiDAR data were calibrated using ground points in calibration site for the higher system accuracy. The accuracy results are ${\pm}15{\sim}30\;cm$ in horizontal and ${\pm}15\;cm$ in vertical. The results show that LiDAR system has capability for precise DEM and contour generation, 3D urban modeling and engineering design.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.42 no.2
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• pp.97-103
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• 2006

The integrated navigation system(INS) for fishing boat which organized the marine radar, global positioning system(GPS) compass, automatic identification system(AIS), echo sounder, GPS and electronic nautical chart(ENC) was manufactured to reduce the marine accidents of fishing boats occurred frequently at coastal and offshore. The application possibility of INS for fishing boat was examined for basic experiments in the sea. Integration display of various information, such as other vessel's behavior, depth, own vessel's position etc. was done to help the operate user who understood the circumstance around own boat. Therefore, the system will be utilized as a useful equipment for safety voyage and fishing work on the fishing ground.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.118-128
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• 2017

In this study, we propose a real time inertial navigation system/global positioning system (INS/GPS) integrated smoothing algorithm based on an extended Kalman filter (EKF) and a position damping loop (PDL) for synthetic aperture radar (SAR). Integrated navigation algorithms usually induce discontinuities due to error correction update by the Kalman filter, which are as detrimental to the performance of SAR as the relative position error. The proposed smoothing algorithm suppresses these discontinuities and also reduces the relative position error in real time. An EKF estimates the navigation errors and sensor biases, and all the errors except for the position error are corrected directly and instantly. A PDL activated during SAR operation period imposes damping effects on the position error estimates, where the estimated position error is corrected smoothly and gradually, which contributes to the real time smoothing and small relative position errors. The residual errors are re-estimated by the EKF to maintain the estimation performance and the stability of the overall loop. The performance improvements were confirmed by Monte Carlo simulations. The simulation results showed that the discontinuities were reduced by 99.8% and the relative position error by 48% compared with a conventional EKF without a smoothing loop, thereby satisfying the basic performance requirements for SAR operation. The proposed algorithm may be applicable to low cost SAR systems which use a conventional INS/GPS without changing their hardware configurations.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.341-348
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• 2013

A location estimation algorithm based on the sea-surface beacon is proposed in this paper. The beacon is utilized to provide ultrasonic signals to the underwater vehicles around the beacon to estimate precise position of underwater vehicles (ROV, AUV, Diver robot), which is named as USBL (Ultra Short Baseline) system. It utilizes GPS and INS data for estimating its position and adopts DWT (Discrete Wavelet Transform) de-noising filter and UKF (Unscented KALMAN Filter) elaborating the position estimation. The beacon system aims at estimating the precise position of underwater vehicle by using USBL to receive the tracking signals. The most important one for the precise position estimation of underwater vehicle is estimating the position of the beacon system precisely. Since the beacon is on the sea-waves, the received GPS signals are noisy and unstable most of times. Therefore, the INS data (gyroscope sensor, accelerometer, magnetic compass) are obtained at the beacon on the sea-surface to compensate for the inaccuracy of the GPS data. The noises in the acceleration data from INS data are reduced by using DWT de-noising filter in this research. Finally the UKF localization system is proposed in this paper and the system performance is verified by real experiments.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.157-165
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• 2007

In this research, a vertical alignment analysis algorithm was developed. The developed algorithm used acquired data from a vehicle with multiple sensors such as a global positioning system (GPS) an inertial navigation system (INS), and a distance measuring unit (DMI) to collect information about vehicle position and altitude. The vertical alignment analysis algorithm includes the identification of vertical tangent sections, the beginning and ending points of vertical curves, and the calculation of length of vortical curves. Also, the algorithm can help build models for vertical tangent sections and vertical curve sections. In order to verify the algorithm, a field survey was conducted at an actual highway section and the result of the field survey was compared to a highway CAD drawing.

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.91-97
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• 2003

The design of Graphic Information System(GIS) in various applications is suffering from the difficulty of data acquisition, which is labor-intensive and time consuming. In order to provide the spatial data rapidly and accurately, 4S-Van, a prototype mobile mapping system, has been developed. The 4S-Van consists of 1)Global Positioning System(GPS), Inertial Navigation System(INS) for estimating the geographic position and attitude of the moving van, i.e.,(x, y, z) and the direction of the Van, 2) Charge Coupled Device(CCD) camera and laser scanner for capturing images and for measuring depth from geographic objects, and 3) External Synchronization Device(ESD) and industrial PC for synchronizing data from GPS/INS/CCD camera and for storing the data. In this paper, we present the design and implementation of the proto-Dpe 4S-Van system for spatial data acquisition for various GIS applications.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.423-427
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• 2010

현재 GPS/INS 운영 방법은 일정한 범위 내에 GPS 지상기준국을 설치하도록 되어있다. 그러나 촬영지역이 넓을 경우나 작업의 우선순위 등에 따라 지상기준국의 운영이 곤란한 상황이 발생할 수 있으며, 작업자의 실수, 수신기의 오류 등으로 지상기준국을 항상 안정적으로 운영하기 어렵다. 이에 본 연구에서는 국토지리정보원의 GPS 상시관측소를 활용하여 항공레이저측량 원시자료를 구축하고, 지상 기준국을 사용한 결과와의 비교를 통해 기준국이 항공레이저측량 결과에 미치는 영향을 분석하고자하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.65-72
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• 2010

In this study, the performances of a medium grade IMU which is aimed for Mobile Mapping System and a low grade IMU for pedestrian navigation are analyzed through simulations under GPS signal blockage. In addition, an analysis on the accuracy improvement of barometer, electronic compass, or multi-sensor(combination of barometer and electronic compass) to correct medium grade or low grade IMU errors in the situation of GPS signal blockage is performed. With the medium grade IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 5m when the block time is over 30 seconds. When we correct IMU with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 60 seconds. In addition, barometer is more effective than the electronic compass when they are combined. In case of low grade IMU like MEMS IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 20m when the block time is over 15 seconds. When we correct INS with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 15 seconds in simulation results. On the contrary to medium grade IMU, electronic compass is more effective than the barometer in case of low velocity such as pedestrian navigation. It is expected that the analysis suggested a method to decrease position or attitude error using aided sensor integration when MMS or pedestrian navigation is operated under 1he environment of GPS signal blockage.