• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.263-273
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• 2008

The precision of sensors' position is particularly important in the application of road extraction or digital map generation. In general, the various ranging solution systems such as GPS, Total Station, and Laser Ranger have been employed for the position of the sensor. Basically, the ranging solution system has problems that the signal may be blocked or degraded by various environmental circumstances and has low temporal resolution. To overcome those limitations a IMU/range integrated system could be introduced. In this paper, after pointing out the limitation of extended Kalman filter which has been used for workhorse in navigation and geodetic community, the two sampling based nonlinear filters which are sigma point Kalman filter using nonlinear transformation and carefully chosen sigma points and particle filter using the non-gaussian assumption are implemented and compared with extended Kalman filter in a simulation test. For the ranging solution system, the GPS and Total station was selected and the three levels of IMUs(IMU400C, HG1700, LN100) are chosen for the simulation. For all ranging solution system and IMUs the sampling based nonlinear filter yield improved position result and it is more noticeable that the superiority of nonlinear filter in low temporal resolution such as 5 sec. Therefore, it is recommended to apply non-linear filter to determine the sensor's position with low degree position sensors.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.186-196
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• 1999

The CPS provides data with long-term stability independent of passed time and the INS provides high-rate data with short-term stability. By integrating these complementary systems, a highly accurate navigation system can be achieved. In this paper, a loosely-coupled GPS/INS integration system is designed. It is a simple structure and is easy to implement and preserves independent navigation capability of GPS and INS. The integration system consists of a NCU, an IMU, a GPS receiver, and a monitoring system. The navigation algorithm in the NCU is designed under the multi-tasking environment based on a real-time kernel system and the monitoring system is designed using the Visual C++. The integrated Kalman filter is designed as a feedback formed 15-state filter, in which the states are position errors, velocity errors, attitude errors and sensor bias errors. The van test result shows that the integrated system provides more accurate navigation solution then the inertial or the GPS-alone navigation system.

• Journal of Advanced Navigation Technology
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• v.16 no.5
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• pp.738-743
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• 2012

Kalman filter is generally used in INS/GPS integrated navigation filter. However, the INS with low performance inertia sensor can not find accurate azimuth in initial alignment stage because sensor noise level is too large compare to Earth rotation rate, therefore the performance and stability of Kalman filter can not be guaranteed. In this paper, the extended Kalman filter and particle filter combined filter structure which can be overcome large initial azimuth error is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.633-643
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• 2005

An unmanned aerial vehicle (UAV) is an aircraft controlled by .emote commands from ground station and/o. pre-programmed onboard autopilot system. A navigation system in the UAV provides a navigation data for a flight control computer(FCC). The FCC requires accurate and reliable position, velocity and attitude information for guidance and control. This paper proposes an ADGPS/INS integrated navigation system for a UAV. The proposed navigation system comprises an attitude determination GPS (ADGPS) receive., a navigation computer unit, and a low-cost commercial MEMS inertial measurement unit(IMU). The navigation algorithm contains a fault detection and isolation (FDI) function fur integrity. In order to evaluate the performance of the proposed navigation system, two flight tests were preformed using a small aircraft. The first flight test was carried out to confirm fundamental operation of the proposed navigation system and to check the effectiveness of the FDI algorithm. In the second flight test, the navigation performance and the benefit of the GPS attitude information were checked in a high dynamic environment. The flight test results show that the proposed ADGPS/INS integrated navigation system gives a reliable performance even when anomalous GPS data is provided and better navigation performance than a conventional GPS/INS integration unit.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.525-528
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• 2003

In this paper, we present a novel idea to integrate low cost Inertial Measurement Unit(IMU) and Differential Global Positioning System (DGPS) for Telematics applications. As well known, low cost IMU produces large positioning and attitude errors in very short time due to the poor quality of inertial sensor assembly. To conquer the limitation, we present a bimodal approach for integrating IMU and DGPS, taking advantage of positioning and orientation data calculated from CCD images based on photogrammetry and stereo-vision techniques. The positioning and orientation data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method that can provide accurate position and attitude information for extended period for non-aided GPS information.

• 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.

• 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 KIEE Conference
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• 2008.04a
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• pp.197-198
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• 2008

A software platform which is able to evaluate the performances of a GPS/INS integrated system has been developed in this paper. And it consists of four parts including GUI(Graphic User Interface) part, GPS part, INS part and integrated filter part. It basically offers the loosely, tightly and deeply coupled GPS/INS algorithms, and many design parameters can be changed by users via GUI. Each functions of the platform has been confirmed with GPS signals and IMU data from commercial simulators.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.31-37
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• 2012

Because of road construction and expansion, Update of the road traffic facilities DB is steadily increased each year, and, Increasing drivers and cars, safety signs for traffic safety are required management and additional installation continuously. To update Safety Sign database promptly, we have developed auto recognition function of safety sign, and analyzed coordinates accuracy. The purpose of this study was to propose methods to update about road traffic facilities efficiently. For this purpose, omni-directional camera was calibrated for acquisition of 3-dimensional coordinates, integrated GPS/IMU/DMI system and applied image processing. In this experiment, we proposed a effective method to update database of road traffic facilities for digital map.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.117-126
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• 2001

We have developed the Mobile Multi Sensor System(MMSS) for the data construction of 4S application and for basic technology acquisition of mobile mapping system in Korea. Using this MMSS, we will collect the information of road and road facilities for DB creation and also construct the Digital Elevation Model(DEM) as ancillary data in urban area. The MMSS consist of the integrated navigation sensor, DGPS & IMU, and digital CCD camera set. In the S/W aspect, we developed the post-processing components for extracting the 3D coordinate information (Spatial Information) and the client program for the MMSS user group. In this paper, we will overview the MMSS constitution and post-processing program, and introduce the utilization plan of MMSS.