• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1802_1803
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• 2009

위치추정은 현재 이동로봇 분야에서 매우 중요하게 다루어지는 문제이다. RFID 위치추정 시스템은 저렴하고, 오차누적의 위험이 없고, map과 같은 사전정보의 제약이 없기에 범용적으로 사용될 수 있다. 하지만 RFID 위치추정에 있어, tag들의 서로 다른 인식거리 차이는 위치추정의 오차를 증폭시키는 역할을 한다. 따라서 이 논문에서는 이를 극복하기 위해 tag들의 인식거리 정보를 활용하여 위치추정을 수행한다. 또한 보다 정확한 위치추정을 위해, 송신신호 전력조절을 통하여, 인식거리를 조절하는 방법을 사용한다. 이들의 성능은 simulation을 통해서 확인하였다.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.431-443
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• 2010

In this paper, we propose a range-free localization method that can improve the estimation accuracy of Approximate Point in Triangle(APIT), which is the representative localization method for low cost wireless sensor networks. Specifically, we propose extended-APIT(e-APIT) method, which minimizes the error in deciding whether an object is in an area formed by three beacons. We also propose a way to improve the localization by narrowing down the potential localization area using the signals from neighboring beacons. According to the simulation performed, the proposed e-APIT method demonstrated noticeable accuracy improvement over the conventional APIT method.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.511-518
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• 2023

Accurate ranging is one of the key factors in the test and evaluation process of underwater vehicles. In particular, when estimating range using Time of Arrival (ToA) values, signals such as Linear Frequency Modulation (LFM), a chirp signal, are highly applicable due to their correlated nature. However, in a Doppler shift environment with mobility, measurement errors may occur due to the range-Doppler coupling effect. In this paper, we propose a signal that compensates for the distance-Doppler coupling effect to reduce the measurement error of the arrival time value. The proposed signal is constructed by superimposing two types of LFM signals, and the range-Doppler coupling effect can be minimized. Through simulations, it is confirmed that the proposed signal is a way to compensate for the distance-Doppler coupling effect in the distance estimation of underwater mobile bodies, reducing the measurement error of the arrival time value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.453-461
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• 2012

This paper proposes an improved phase estimation method for AM(Amplitude Modulation) range measurement system. The previous phase estimation method induces errors by Doppler shift of a moving target. The proposed method compensates phase estimation error through the ADC(Adaptive Doppler Correction) to take the Doppler shift, thus can improve distance measurement accuracy. When compared with the previous method through simulation results, the Doppler shift compensation and accuracy are improved by 94.7% and 50%, respectively. Target distance error in an acoustic tank is estimated to be 7.7cm, which confirms that the proposed method can be used to estimate the distance in the marine environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.104-113
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• 2022

In this paper, we propose deep learning-based target distance and velocity estimation technique for OFDM radar systems. In the proposed technique, the 2D periodogram is obtained via 2D fast Fourier transform (FFT) from the reflected signal after removing the modulation effect. The periodogram is the input to the conventional and proposed estimators. The peak of the 2D periodogram represents the target, and the constant false alarm rate (CFAR) algorithm is the most popular conventional technique for the target's distance and speed estimation. In contrast, the proposed method is designed using the multiple output convolutional neural network (CNN). Unlike the conventional CFAR, the proposed estimator is easier to use because it does not require any additional information such as noise power. According to the simulation results, the proposed CNN improves the mean square error (MSE) by more than 5 times compared with the conventional CFAR, and the proposed estimator becomes more accurate as the number of transmitted OFDM symbols increases.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.209-216
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• 2023

This paper aims to develop a model to estimate the paint thickness in a shipyard spray painting according to changes of spraying distance and speed. We acquired the experimental datasets of five different conditions with respect to the spraying distance and speed using a painting robot. In addition, we applied a preprocessing step to handle noises which might be caused by various reasons such as a nozzle damage. Our method is to transform a thickness function of a specified spraying distance and speed into another function of an unknown spraying and speed. We observed that the proposed method shows more stable and more accurate predictions compared with an artificial neural network-based approach.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.21-29
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• 2011

This paper presents a method that estimates distance and velocity of an object with reliability regardless of maneuver status of the target in stereo vision system. A stereo vision system can calculate a distance with disparity from left and right images. However, the distance estimation error may occur due to quantization error of image pixel. A sub-pixel interpolation method minimizes the quantization error and estimates accurate disparity with real value. Extended Kalman filter (EKF) was used to minimize the error covariance and estimate the object's velocity. However, divergence problem occurs due to model uncertainty when a target maneuvers highly, which makes the estimation error increase. In this paper, we propose a virtual model extended Kalman filter (VMEKF) method that minimizes the processing time and provides reliable estimation ability regardless of maneuver status. Computer simulations and experimental results in real road environments demonstrate that the proposed method gives a reliable estimation performance and reduces processing time under various maneuver status while comparing other estimation filters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.640-651
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• 2016

We propose an effective ToA-based localization method considering accuracy in indoor environments. The purpose of the localization system is to estimate the coordinates of the geographic location of target device. In indoor environments, accurately estimating the location of a target device is not easy due to various errors. The accuracy of wireless localization is influenced by NLOS errors. ToA-based localization measures the location of a target device using the distances between a mobile device and three or more base stations. However, each of the NLOS errors along a distance estimated from a target device to a base station is different because of dissimilar obstacles. To accurately estimate the target's location, an optimized localization process is needed in indoor environments. In this paper, effective ToA-based localization method process is proposed for improving accuracy in wireless sensor networks. Performance evaluations are presented, and the experimental localization system results are proved through comparisons of various localization methods with the proposed methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.71-76
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• 2019

Research on indoor location tracking technology using smartphone is actively being carried out. Especially, the movement distance of the smartphone should be accurately measured and the movement route of the user should be displayed on the map. Location tracking technology using sensors mounted on smart phones has been used for a long time, but accuracy is not good enough to measure the moving distance of the user using only the sensor. Therefore, when the user moves the smartphone in a certain posture, it must research and develop an appropriate algorithm to measure the distance accurately. In this paper, we propose a method to reduce moving distance estimation error by removing user 's foot shape by limiting the screen of smartphone in pyramid - based optical flow estimation method.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.78-80
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• 1998

본 논문은 일차원의 시계열 데이터를 입력을 하여 위상공간 재구성 과정을 거쳐 다차원 위상공간상에서 프랙탈 차원을 계산하는 효율적인 방법을 제안한다. 프랙탈 차원의 추정에 소요되는 계산량을 줄이기 위해 로그 연산을 비트 연산으로 대체하고, 거리계산의 순서를 바꿈으로써 위상공간의 차원에 무관한 상수 시간의 계산복잡도를 가지는 알고리즘을 구현하였다. 또한 최소절단자승 추정기법을 적용하여 로그-로그 그래프 상에서의 기울기 추정을 함으로써 프랙탈 차원의 추정치에 대한 정확도를 높였다. 참값이 알려진 시계열 데이터에 대한 차원 추정 실험을 통하여 제안된 방법의 정확성을 보였다.