• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1729-1735
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• 2009

The hierarchical routing could cause a lot of energy consumption for transferring data by assigning hierarchical routes although actual nodes could be located in physically near spots. Also, when Node Failure or Association Error occurs, the Hierarchical routing could waste more energy to deliver the control messages. This paper evaluate performance of SHP(Shortest Hop Routing) algorithm that suggests short-cut routing algorithm using NL(Neighbor List) and Redirect_ACK message to improve problem of hierarchical routing algorithm. We do a computer simulation by the size of network, deployment of sensor nodes, sink position and POS. As a result of simulation, SHP has better performance than Zigbee Hierarchical routing and HiLow.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.294-300
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• 2005

Generally, traditional approaches to track the target position are to estimate ranges and bearings by 2-D MUSIC (MUltiple 519na1 Classification) method. and to associate estimates of 2-D MUSIC made at different time points with the right targets by JPDA (Joint Probabilistic Data Association) filter in the near field. However, the disadvantages of these approaches are that these have the data association Problem in tracking multiple targets. and that these require the heavy computational load in estimating a 2-D range/bearing spectrum. In case multiple targets are adjacent. the tracking performance degrades seriously because the estimate of each target's Position has a large error. In this paper, we proposed a new tracking algorithm using Position innovations extracted from the senor output covariance matrix in the near field. The proposed algorithm is demonstrated by the computer simulations dealing with the tracking of multiple closing and crossing targets.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.327-332
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• 2006

In airborne gravimetry, there are two data streams. One is the specific force measured by an air/sea gravimeter or accelerometers, the other is kinematic acceleration measured by DGPS. And the difference of them provides the gravity disturbance information. To satisfy the requirement of most applications, an accuracy of 1mGal $(1mCal=10^{-5}m/s^{2})$ with a spatial resolution of 1km is the aim of current airborne gravimetry. There are two different methods to derive the kinematic acceleration. The generally used method is to differentiate the position twice, and the position can be calculated by commercial DGPS software. The main defect of this method is that integer ambiguities need to be fixed to get the precise position solution, but it's not a trivial thing for long base line. And to fix integer ambiguities, the noisier iono-free measurement is used. When differentiation is applied, noise is amplified and will influence the accuracy of acceleration. The other method is to get carrier phase acceleration by differentiate the carrier phase first, and then using the acceleration of GPS satellite to derive the vehicle acceleration. The main advantages include that fixing integer ambiguities is not needed anymore, position can be relaxed to about 10 meters, and smoother acceleration can be got since iono-free measurement is not needed. In some literatures, it's considered that the dynamic performance of the second method is inferior to that of the first. Through analysis, it is found that the performance degradation in dynamic environment results from the simplification of the GPS carrier phase observable model. And an iterative algorithm is presented to compensate the model error. Using a dynamic GPS data from an aeromagnetic survey, the importance of this compensation is showed at last.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.241-244
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• 1997

A dead reckoning navigation system is developed for autonomous mobile robot localization. The navigation system was implemented by novel sensor fusion using a Kalman filter. A differential encoder and the gyroscope error models are developed for the filter. An indirect Kalman filter scheme is adopted to reduce the computational burden and to enhance the navigation system reliability. The filter mutually compensates the encoder errors and the gyroscope errors. The experimental results show that the proposed mobile . robot navigation algorithm provides the reliable position and heading angle of the mobile robot without any help of the external positioning systems.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.540-543
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• 1997

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of the path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force, and external disturbance are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the usage of vision system makes mobile robot compensate the cumulative location error which exists when relative sensor like encoder is used to locate the position of mobile robot. The effectiveness of the proposed control scheme is shown through computer simulation.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.505-507
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• 2004

This paper presents a measurement of ZMP using FSR sensors, and then the ZMP control with measured ZMP on single leg. ZMP is mostly used as standard evaluation of stability of a humanoid robot. The ISHURO has 5 sensors which are mounted at each corner and center of a sole. ZMP is computed using a model of a humanoid robot and information from the joint encoders. And we may able to use measurement data from FSR sensors at the robot feet. IP(Integration Proportional) control algorithm is applied to position control of ZMP that is an error of desired ZMP between measured ZMP.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.623-626
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• 1991

Crucial to the success of the vector control scheme without speed sensor is up to computing instantaneous position of the rotor flux. In tracing this flux depending on the machine parameter, variations of those factor lead to the non-linear charlcteristic between I/O value and decrease overall efficiency of the vector control scheme. This paper, using recursive least square method estimating instantaneous value of the machine speed and parameter from the shift of current and voltage, proposes an algorithm for compensating the I/O error of the scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.116-124
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• 2011

A service robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to special landmarks which are developed as high gain reflection material and coded array associations. In this paper, the authors propose a set of indices to evaluate the accuracy of self-localizing methods using the selective reflection landmark and infrared projector, and the indices are derived from the sensitivity enhancement using 3D distortion calibration of camera. And then, the accurarcy of self-localizing a mobile robot with landmarks based on the indices is evaluated, and a rational way to minimize to reduce the computational cost of selecting the best self-localizing method. The simulation results show a high accuracy and a good performance.

• 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.