• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2365-2367
• /
• 2000

The deterministic errors of semiconductor gyros and accelerometers must be estimated and compensated to develop the low-cost IMU using them. Generally, the dominant errors of the low-cost IMU are bias and misalignment errors. Bias is sensitive to temperature. Therefore, in this paper, the effect on temperature of bias is analyzed and temperature compensation are carryed out. It is shown by experiment that the compensation is efficient.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.990-994
• /
• 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
• /
• v.27 no.2
• /
• pp.249-260
• /
• 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
• /
• v.14 no.8
• /
• pp.774-778
• /
• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2004.08a
• /
• pp.45-53
• /
• 2004

In this paper, an INS compensation algorithm for auto sailing system is proposed, where low cost IMU (Inertial Measurement Unit) is used for measuring the accelerometer data. First, we denote the basic INS algorithm with IMU and show that how to compensate the error of position by using low cost IMU. Second, in considering the ship's characteristic and ocean environments, we consider with a factor as a periodic external disturbance which effects to the exact position. To develop the compensation algorithm, we use a repetitive method to reduce the external environment changes. Lastly, we verify the proposed algorithm by using experiments results.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.525-528
• /
• 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 Institute of Control, Robotics and Systems
• /
• v.14 no.5
• /
• pp.502-510
• /
• 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.

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

• ETRI Journal
• /
• v.26 no.5
• /
• pp.497-500
• /
• 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.

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