• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.218-227
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• 2017

In this paper, an algorithm to calculate both bearing and distance error for target detection and localization is proposed using the Cramer Rao lower bound to estimate the minium variance of their error in DOA (Direction Of Arrival) estimation. The performance of arrays in detection and localization depends on the accuracy of DOA, which is affected by a variation of SNR (Signal to Noise Ratio). The SNR is determined by sonar parameters such as a SL (Source Level), TL (Transmission Loss), NL (Noise Level), array shape and beam steering angle. For verification of the suggested method, a Monte Carlo simulation was performed to probabilistically calculate the bearing and distance error according to the SNR which varies with the relative position of the target in space and noise level.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.74-79
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• 2012

Scalar quantification of the angular prediction error covariance matrix is considered for characterizing tracking performances in phased array radar tracking. Specifically, the maximum eigenvalue and the trace of the covariance matrix are examined in terms of consistency in parameterizing the probability of detection, taking antenna beam-pointing losses into account, and it is shown numerically that the latter is more consistent.

• Journal of Drive and Control
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• v.14 no.2
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• pp.9-15
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• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.155-163
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• 2012

The geometrical and electrical errors of array sensors can severely degrade the performance of array sensor system. Various calibration techniques are developed to alleviate this problem. In this paper, two different calibration methods with respect to location, gain and phase of array sensors are presented. One method applies the first-order Taylor series expansion to approximate the true steering vector from the nominal values of array sensors. Then a set of equations is formed by using the null characteristics of the MUSIC spectrum to estimate errors of location, gain and phase of array sensors. Another method estimates these errors based on the data covariance matrix of pilot sources. From the simulations, it is demonstrated that two calibration algorithms calibrated an array system successfully. In addition to that, Fistas and Manikas's algorithm is more robust against noise than Ng and Lie's one when SNR is from 10dB to 50dB.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.599-605
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• 2017

For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.299-311
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• 2011

In this paper, we have identified the system instability factors in a bistatic radar system using pulse chasing and considered their effects on the bistatic receiver's MTI(Moving Target Indication) improvement performance. The pulse chasing is a scan method that searchs a restricted area on the transmit pulse-to-pulse basis and the MTI filter is a signal processing that separates a target from some kinds of interferences such as clutter using small number of transmit pulses. Ideal MTI processing performance, e.g., clutter attenuation and improvement, has been limited by the property of the clutter itself, however, the MTI performance in a proposed bistatic receiver configuration could be affected by the receiving beam pointing error during pulse chasing scanning. Also, for the bistatic receiver, we have defined other system instability factors, which result from the time synchronization error, COHO's phase error, the frequency/phase synchronization error, and have analyzed their effects on the system performance improvement.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.11-19
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• 2019

The waveguide slotted active phased array radar is characterized in that the beam is tilt in a specific direction when the feeding position of the antenna is not in the center of the antenna. If the beam deflection phenomenon is not properly compensated, error bias is generated in the target information collected by the radar, and the target accuracy is lowered. In this paper, we describe a technique to compensate the error of the target information that is collected in the active phased array radar of the waveguide slot type instead of the center of the antenna.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.452-453
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• 2008

전 차륜 조향 굴절차량의 자동안내제어를 위한 기준경로와의 편차 되먹임 방식은 곡선경로에서 발생하는 정상상태 오차를 줄이기 어렵다. 본 논문은 이 차량의 자동안내제어의 성능향상을 위한 전향보상기 설계에 대해 기술한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.133-139
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• 1997

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is propored a learning controller consisting of two neural network-fuzzy based on independent resoning and a connection net with fixed weights to simply the neural network-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.163-167
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• 2008

본 논문에서는 자계기반 무인주행 차량용 자계위치 인식장치의 성능향상에 대하여 다룬다. 자계위치인식장치는 자석의 위치를 검출하는 센서이다. 기존의 자계위치인식장치는 센서사이에 자석이 놓여있는 경우 자석의 위치를 검출하지 못하는 단점을 지니고 있다. 이는 자석의 위치검출 정밀도가 떨어지고 차량이 무인주행 시 조향각 오차가 발생한다. 따라서 본 논문에서는 기존의 자계위치 인식장치의 문제점을 극복하고 센서사이의 자석위치도 검출할 수 있는 방법을 제안한다. 제안하는 방법의 유용성을 입증하기 위하여 실험을 행하고 결과를 분석하였다.