• 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 Advanced Navigation Technology
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• v.20 no.4
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• pp.314-320
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• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.1
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• pp.43-52
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• 2018

In recent years, the need of high accuracy navigation for vehicles has increased due to the development of autonomous driving vehicles and increase in land transportation convenience. This study is performed for vehicle users to achieve a performance of centimeter-level positioning accuracy by utilizing Compact Network Real-time Kinematic (RTK) that is applicable as a national-level infrastructure. To this end, medium-baseline RTK was implemented in real time to estimate accurate integer ambiguities between reference stations for reliable generation of Network RTK correction using the linear combination of carrier-phase observations and L1/L2 pseudo-range measurements. The residual tropospheric error was estimated in real time to improve the accuracy of double-differenced integer ambiguity resolution between network configuration reference stations that have at least 30 km or longer baseline distance. In addition, C++ based software was developed to enable real-time generation and broadcasting of Compact Network RTK correction information by utilizing an accurately estimated double-differenced integer ambiguity values. As a result, the horizontal and vertical 95% accuracy was 2.5cm and 5.2cm, respectively, without performance degradation due to user's position change within the network.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.633-638
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• 1988

In this paper, a zero-velocity update technique to improve navigation accuracy of a SDINS(Strapdown Inertial Navigation System) has been studied. An indirect feedback Kalman filter which includes SDINS error equations based on a quaternion between body-fixed frame and local level navigation frame is employed for processing zero-velocity updates in an on-board navigation filter. Simulation results for land-mobile vehicle show that the zerovelocity update technique make a significant contribution to improving SDINS performance without any external aids.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.81-88
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• 1994

The CNS(Car Navigation System) is used more generally in driver aid system than ALV(Auto nomous Land Vehicle) research area. In this paper we developed a new position tracking algorithm for the Global Path Planning in the CNS. In japan, CNS is already well developed and, thesedays they sell CNS products about $400{\sim}500$ thousands per year, and USA and European Communications(EC), too. In Korea, studies of the first generation CNS, which finds current location of a navigating vehicle and displays its location in a Digital-Map with real-time are progressing but still in the beginning step. Therefore a new position tracking algorithm is presented, which reduces vehicle position error dramatically by fusing GPS and dead-reckoning sensors. And the validity of our algorithm is demonstrated by the experimental results with the real car.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.73-74
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• 2015

In the world the interests about a unmanned surface vehicle(USV) are growing up. However it is difficult to launch and recover a USV because of no men on board of USV. And it is more difficult in recovery than launch of USV. So in this research the heaving line launcher was developed to support the recovery of USV easier. And a mock-up was manufactured to validate for adoption to the USV. The muck-up is composed of launcher pipe, remote trigger, air tank, tow shell and heaving line. Tests in land using the mock-up were carried out. The forces by the heaving line launcher to USV were measured by a measuring table during the tests in land. In this paper the development of a mock-up of heaving line launcher, tests in land and the measured forces during tests are presented.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.557-565
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• 2018

For GNSS navigation in urban environment, a novel short delay multipath mitigation algorithm is proposed in this paper. This algorithm detects which satellite's signal is the multipath signal by using the constraint that GNSS receiver is equipped in a ground vehicle, then estimate new position after separating the measurement of that satellite. A criterion for detecting and validating the multipath signal depends on the performance grade of the GNSS receiver and the dynamics of the vehicle. In order to evaluate the proposed algorithm, the real data had been collected at the multipath environment of 4 scenarios. By post-processing the real data with both of the multipath mitigation algorithm in the receiver and the proposed algorithm, it can be checked that the position errors were less than 5 meters except the case that the number of visible satellite is lower than 5.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.967-976
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• 2016

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.56.1-56
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• 2001

Initial attitude error is one of the large error sources in the navigation errors of SDINS. And it is important to decide the initial attitude of SDINS. The method, like a self-alignment or a transfer alignment method, is required to a precise INS. If we do not have a precise INS, we should get large attitude error. After performing the initial alignment, a vehicle has the initial attitude error. Therefore, it results in navigation error due to the initial attitude error. But, if we use position information during flight, we could estimate and compensate a vehicle attitude error. So, we can maintain a precise attitude in spite of existing the initial attitude error. Using the uplinked position information from a land-based radar system, the new algorithm estimates the attitude of the SDINS during flight ...

• 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.