• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.990-994
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• 2003

When the low cost IMU is used, the result of the stationary self alignment is not suitable for navigation. In this paper, an in-motion alignment method is proposed to obtain an accurate initial attitude of a low cost IMU based GPS/INS integration system. To design Kalman filter for alignment, large heading error model is introduced. And then Kalman filter is designed to estimate initial attitude error as the indirect feedback filter. In order to assess performance of the alignment method, computer simulations are carried out. The simulation results show that initial attitude error rapidly reduces.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.249-260
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• 2009

The georeferencing accuracy of the sensory data acquired by an aerial monitoring system heavily depends on the performance of the GPS/IMU mounted on the system. The employment of a high performance but expensive GPS/IMU unit causes to increase the developmental cost of the overall system. In this study, we simulate the images and GPS/IMU data acquired by an UAV-based aerial monitoring system using an inexpensive integrated GPS/IMU of a MEMS type, and perform the image georeferencing by applying the aerial triangulation to the simulated sensory data without any GCP. The image georeferencing results are then analyzed to assess the accuracy of the estimated exterior orientation parameters of the images and ground points coordinates. The analysis indicates that the RMSEs of the exterior orientation parameters and ground point coordinates is significantly decreased by about 90% in comparison with those resulted from the direct georeferencing without the aerial triangulation. From this study, we confirmed the high possibility to develop a low-cost real-time aerial monitoring system.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.774-778
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• 2008

The inaccuracy of inertial sensors used in low cost IMU's limits the usage to ARS, at best. Sensor fusion technologies are widely used to overcome this problem. GPS is the most popular secondary sensor, but GPS alone cannot fully compensate the IMU errors in the initial alignment process and rectilinear flights. This paper presents a new concept of aiding the low cost IMU with the sun line of sight vector. The simulation and experimental results in this paper proves that aiding of INS/GPS with the sun line of sight vector increases the observability and improves accuracy remarkably.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.502-510
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• 2008

UAVs(Unmanned Aerial Vehicles) have many applications in military and commercial areas. The flight control system of UAVs is more important than manned aircraft's because the mission of UAVs must be operated without a human pilot. But very heavy and expensive navigation system makes it difficult to develop UAV flight control system. In this research, GPS/IMU integrated navigation filter was developed for light weight/low cost flight control system of small UAVs. With this navigation filter, full flight control system which has real time operating capability has been developed. The performance of the flight control system is basically checked by HILSIM (Hardware In the Loop SIMulation). Finally, the flight control system is verified by showing performance test result under real flight environment.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.91-91
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• 2000

In this paper, the error compensation method of the attitude reference system with low-cost IMU is proposed. In general, the attitude error calculated by gyro grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound by accelerometer mixing algorithm and the heading angle can be aided by GPS velocity information. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by medium-grade IMU, LP-81.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.18-20
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• 2021

In order to prevent collision accidents of ships, which has been increasing recently, research on artificial intelligence-based autonomously operated ships (Maritime Autonomous Surface Ship, MASS) is underway. However, most of the studies related to autonomous ships mainly target medium-to-large ships due to the size and cost of the autonomous navigation system, and the sensors used here have a problem in that it is difficult to mount them on small ships. Therefore, this paper provides a path tracking system equipped with GPS and IMU sensors for autonomous operation of small ships. GPS and IMU sensors are utilized to determine the exact position of the vessel, which allows the proposed system to manually control the small vessel model to create a path and then when the small vessel travels the same path. Use the Pure Pursuit algorithm to follow the path. As a result, In this research, it is expected that a lightweight and low-cost sensor can be used to develop an autonomous operation system for small ships at low cost.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.271-275
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• 2006

This paper describes the design and realization of full attitude system based on MEMS IMU and GPS carrier phase. The work can be divided into two parts: First, initial heading is determined by using two GPS receivers. And this paper discusses the usage of space geometry conditions to reduce the range of ambiguity search. The method presented in this paper was tested on the static. On the static condition, an accuracy better than 0.06 degrees for heading for 3.48m long baseline has been achieved. Integration of GPS and low cost MEMS IMU are used to realize the real-time heading attitude system. Second, level attitude (pitch and roll) is determined using the method of frequency-velocity for the feedback control. At the same time, the method using the attitude based on MEMS IMU to help determination of the range of ambiguity search is proposed. The results done on the sea show that an alternative means to provide real-time, cost-effective, accurate and reliable attitude information for attitude surveys. Though motivated by a big ships application, the design can be applied to other vehicles.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.5-141
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• 2001

An attitude GPS receiver with 3 antennas obtains 3-dimensional attitude using GPS carrier phase measurement INS obtains the 3 dimensional navigation solution for IMU consisting of accelerometers and gyro. Ground-alignment process for the low -cost INS cannot be performed well due to the large sensor noise. Using the standard GPS receiver, however, continuous in-flight alignment for the INS becomes possible, and consequently, the errors in IMU sensors and navigation solution can be compensated. Especially with attitude measurement from the attitude GPS receiver, the compensation of errors in gyroscope and attitude would be done respite of the vehicle´s dynamics and their error covariance would be reduced. This paper presents ...

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.133-139
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• 2007

An unmanned ground vehicle can perform its mission automatically without human control in unknown environment. To move up to a destination in various surrounding situation, navigational information is indispensible. In order to be adopted for an unmanned vehicle, the navigation box is small, light weight and low power consumption. This paper suggests navigation system using a low grade MEMS IMU for supplying position, velocity, and attitude of an unmanned ground vehicle. This system consists of low cost and light weight MEMS sensors and a GPS receiver to meet unmanned vehicle requirements. The sensors are basically integrated by loosely coupled method using Kalman filter and internal algorithms are divided into initial alignment, sensor error compensation, and complex navigation algorithm. The performance of the designed navigation system has been analyzed by real time field test and compared to commercial tactical grade GPS/INS system.