• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.115-121
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• 2024

As the radar mounted on a moving platform moves and rotates, the state of the radar's coordinate system also changes. At this time, in order to track target, the target's coordinates should be converted using the platform state measured from the sensor, and tracking performance may deteriorate due to causes such as sensor noise, communication delay, and sensor update cycle. In this paper, to minimize the degradation of tracking performance because of sensor error, we designed a navigation filter to estimate the state of the moving platform and analyzed the effect of improving tracking performance by applying the navigation filter through a simulation test. To design this navigation filter, three filter algorithms were applied and analyzed to confirm the effect of improving platform position and attitude performance for each filter, and the navigation filter designed by applying the highest performance filter algorithm was applied to a tracking simulation test. Finally we confirmed Improvement in tracking performance before and after applying navigation filters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.293-294
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• 2011

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.4
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• pp.244-250
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• 2008

This paper describes the design and implementation of an unmanned ground vehicle (UGV) and also estimates how well autonomous navigation and remote control of UGV can be performed through the optimized arbitration of several sensor data, which are acquired from vision, obstacle detection, positioning system, etc. For the autonomous navigation, lane detection and tracing, global positioning, and obstacle avoidance are necessarily required. In addition, for the remote control, two types of experimental environments are established. One is to use a commercial racing wheel module, and the other is to use a haptic device that is useful for a user application based on virtual reality. Experimental results show that autonomous navigation and remote control of the designed UGV can be achieved with more effectiveness and accuracy using the proper arbitration of sensor data and navigation plan.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.33.4-33
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• 2002

Recently, number of navigation system using GPS and other complementary sensor has been developed to offer high-position accuracy. In this paper, we developed navigation system for mobile robot integrating GPS and DR sensor information provided by fiber optic gyroscopes and encoder information. In the case of short-term applications, integrating this encoder and gyroscope through Kalman filter reliable positioning can be obtained. And for the long-term applications we developed GPS/DR Integration algorithm using Kalman filter

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.171-179
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• 2004

Today, the number of vehicle increased rapidly with the development of modem science technology, and it caused serious problems; traffic jam, accident and pollution etc. One of the solve methods these problems it is necessary to develope the vehicle navigation systems and it is already widely used to in field of military etc. Vehicle navigation system can increase the efficiency of traffic flow and offer at a drivers at a best driving conditions. In the vehicle navigation, most important thing is to measure of correct position. There are classifiable as three types. The first is G.P.S., method at artificial satellites which measures the present position and velocity any time, any where in the world at the same time. Secondly, a vehicle can determine its position and path information with a gyroscope and odometer signal, which is called Dead-Reckoning method. Thirdly, hybrid navigation system is the combined of two methods to make utilize the advantage of each navigation system. In the paper, we are analyzed to characteristics at a gyro sensor and introduce at a composition of hybrid navigation system which is combined with the G.P.S., D.R., and map-matching technique. We analyze deeply for the Map-Matching method and explain the coordinate transformation for G.P.S., and the Hybrid navigation algorithm is developed and experimented. Finally, we conclude and comment about our road test results.

• Aerospace Engineering and Technology
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• v.9 no.1
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• pp.50-59
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• 2010

In this paper, the alignment and navigation results by INGU(Inertial Navigation and Guidance Unit) onboard software and by Inertial Explorer which is a post-processing software specialized for IMU(Inertial Measurement Unit) are compared for identification of inertial sensor error models and estimation of alignment and navigation errors for KSLV-I INGU. For verification of the IMU error estimated by Kalman Filter of Inertial Explorer, the covariance parameters of inertial sensor error model state are identified by using stochastic error model of inertial sensors estimated by Allan variance and the alignment and navigation test with static condition and the land navigation test with dynamic condition are carried out. The validity of inertial sensor model for KSLV-I INGU is verified by comparison the alignment and navigation results of INGU on-board software and Inertial Explorer.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.141-148
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• 2003

This paper presents a rotating ann test for assessment of an underwater hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. The rotating ann tests are conducted in the Ocean Engineering Basin of KRISO, KORDI to generate circular motion in laboratory, where the USBL system was absent in the basin. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.183-189
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• 2020

In emergency rescue situations, the localization accuracy of the rescue requestor is a very important factor in determining the success or failure of the rescue. Indoors where Global Navigation Satellite System (GNSS) is not operated, there is no choice but to use Wi-Fi or LTE signals. However, the performance of the current emergency rescue system utilizing those RF signals is exceedingly low. In this study, the effectiveness of the surface correlation technology using the accumulated signal pattern of RF signals was verified in relation to the emergency localization technology. To validate the proposed system, we configured and tested an emergency rescue scenario in multi-floors building. When the emergency rescue was requested, it was confirmed that the initial localization error was large owing to the short length of the accumulated signal pattern. However, the localization error decreased over time, which eventually led to the accurate location information being delivered to the rescuer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.374-380
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• 2012

In guided missile systems, reducing terminal-position error is the primary objective of the inertial navigation system. As a seeker is used to sense and track a target, the critical function of the inertial navigation system is to provide the seeker with accurate missile attitude information and help the seeker to keep tracking a target continuously. As inertial sensor body and missile body alignment errors are taken into account, it is desirable to minimize the alignment errors between the missile seeker and the attitude of inertial navigation system. Among the alignment errors, this paper addresses the methods of measuring and compensating misalignment between inertial sensor body and housing frame and shows test results of several experiments.