• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.434-436
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• 1997

본 연구에서는 저속에서 발생하는 측정잡음에 대한 문제를 불규칙 확률시스템으로 고려하여 Kalman 필터를 관측자로서 사용하고 고속에서뿐만 아니라 저속에서의 위치와 속도 추정성능을 향상시키고자 한다. Kalman 필터는 확률적 외란을 포함하고 있는 동적시스템에 적용되는 최적상태 추정자이다. 또한 이 Kalman 필터는 외란을 가지는 이산형 실시간 동적 처리 시스템에서 최적의 미지 상태를 추정하기 위해 선형, 불편향, 그리고 최소 오차분산 회귀형 알고리즘을 제공한다. 또한, MRAS(Model Reference Adaptive System) 방법을 이용하여 모터와 부하에 대응되는 기계적 시정수를 동정한다. 이 방법은 기계적인 시정수가 알려지지 않은 시스템에 적용하여 위치와 속도의 추정을 가능하게 하기 위해서이다. 더욱이 동정의 결과를 이용하여 Kalman 필터 알고리즘에 적용한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.667-670
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• 2020

최근에는 증강현실, 로봇공학 등의 분야에서 객체의 위치 검출 이외에도, 객체의 자세에 대한 추정이 요구되고 있다. 객체의 자세 정보가 포함된 데이터셋은 위치 정보만 포함된 데이터셋에 비하여 상대적으로 매우 적기 때문에 인공 신경망 구조를 활용하기 어려운 측면이 있으나, 최근에 들어서는 기계학습 기반의 자세 추정 알고리즘들이 여럿 등장하고 있다. 본 논문에서는 이 가운데 Dense 6d Pose Object detector (DPOD) [11]의 구조를 기반으로 하여 가구의 조립 설명서에 그려진 가구 부품들의 자세를 추정하고자 한다. DPOD [11]는 입력으로 RGB 영상을 받으며, 해당 영상에서 자세를 추정하고자 하는 객체의 영역에 해당하는 픽셀들을 추정하고, 객체의 영역에 해당되는 각 픽셀에서 해당 객체의 3D 모델의 UV map 값을 추정한다. 이렇게 픽셀 개수만큼의 2D - 3D 대응이 생성된 이후에는, RANSAC과 PnP 알고리즘을 통해 RGB 영상에서의 객체와 객체의 3D 모델 간의 변환 관계 행렬이 구해지게 된다. 본 논문에서는 사전에 정해진 24개의 자세 후보들을 기반으로 가구 부품의 3D 모델을 2D에 투영한 RGB 영상들로 인공 신경망을 학습하였으며, 평가 시에는 실제 조립 설명서에서의 가구 부품의 자세를 추정하였다. 실험 결과 IKEA의 Stefan 의자 조립 설명서에 대하여 100%의 ADD score를 얻었으며, 추정 자세가 자세 후보군 중 정답 자세에 가장 근접한 경우를 정답으로 평가했을 때 100%의 정답률을 얻었다. 제안하는 신경망을 사용하였을 때, 가구 조립 설명서에서 가구 부품의 위치를 찾는 객체 검출기(object detection network)와, 각 개체의 종류를 구분하는 객체 리트리벌 네트워크(retrieval network)를 함께 사용하여 최종적으로 가구 부품의 자세를 추정할 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.434-439
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• 2013

It is very difficult to monitor the blind spots that are not recognized by traditional surveillance camera (CCTV) systems, and the surveillance efficiencies are very low though many accidents/events can be solved by the systems. In this paper, the fuzzy logic based sound source localization system using sound strength in the underground parking lot is suggested and the performance of the system is analyzed in order to enhance the stabilization and the accuracy of the localization algorithm in the suggested system. It is confirmed that the localization stabilization of the localization algorithm (SLA_fuzzy) using the fuzzy logic in the suggested system is 4 times higher than that of the conventional localization algorithm (SLA). In addition to this, the localization accuracy of the SLA_fuzzy in the suggested system is 29% higher than that of the SLA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1141-1151
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• 2001

본 논문에서는 효과적으로 선택된 초기 탐색 위치를 이용한 움직임 추정의 고속 알고리즘을 제안하였다. 제안된 알고리즘에서는 2$\times$2화소 블록 평균으로 부표본화 영상에서 움직임 벡터를 얻어 원영상 비율로 확대하고, 주위 블록의 움직임으로부터 예측 움직임 벡터를 구하여, 이 중에서 정합오차가 작은 것을 초기 탐색 위치로 선택한다. 그리고 선택된 초기 탐색 위치를 중심으로 회전 탐색을 시작하여, 연속 소거 알고리즘으로 탐색할 후보 블록을 선택하고, 부분 정합 왜곡 소거법을 사용하여 블록간 정합오차 계산량을 줄이면서, 고속으로 움직임 벡터를 추정한다. 알고리즘의 실제 적용에 있어서는 선택된 초기 탐색 위치를 중심으로 회전 탐색 패턴의 탐색 범위를 조절하거나, 매크로 블록 당 복잡도를 제한하여 계산량을 줄일 수 있다. 실험 결과, 제안된 알고리즘은 전역탐색 블록정합 알고리즘에 대하여 0.2dB 이하의 미소한 평균 PSNR 저하만을 발생하면서, FBMA 복잡도의 3% 이하의 평균 복잡도를 소요하였다. 이것은 3단계 탐색법에 대하여 40% 이하의 계산량이다. 그리고 실험 영상들의 각 프레임에 대해서도 비슷한 성능을 보임을 확인하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.1
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• pp.41-45
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• 2008

This paper deals with the estimation method on the initial pole position of a z-axis permanent magnet linear synchronous motor(PMLSM) without magnetic pole sensors such as Hall sensors. The proposed method takes account of the gravitational force at z-axis and also the load conditions. The algorithm consists of two steps. The first step is to approximately estimate the initial q-axis by monitoring the movements due to the test current at predefined different test q-axes. The second step is to estimate the real q-axis as accurately as possible by using the outputs corresponding to torques due to the test current at three different test q-axes in order to avoid the effect of load mass variations. Experimental results on the z-axis PMLSM show good estimation characteristics of the proposed method irrespective of load mass conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5C
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• pp.472-478
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• 2010

In the environment of wireless communication system of IEEE 802.15.3a UWB standard, the angle of arrival(AOA) estimation technique for the indoor wireless positioning algorithms, based on the AOA parameter estimation which fits well for the wireless communication channel and shows high estimation accuracy, is proposed. After the UWB signal model, based on the IEEE 802.1.3a standard, is constructed, the average weighted MUSIC technique is proposed, which shows better estimation accuracy than those of conventional estimation technique. Through the simulation studies, the environment of the indoor wireless positioning system including the IEEE 802.15.3a channel is configured and we demonstrate better estimation results by the proposed AOA estimation technique than those from the conventional method.

• Journal of KIISE
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• v.42 no.2
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• pp.264-271
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• 2015

The general way to use a triangulation method is based on PTMP communication between an object and wireless modules in an environment, which is established by more than three wireless modules, to recognize the location of an object. Thus, this method has a problem that the PTMP-based system can only be applied in an environment where the wireless infra is already established. In order to solve this problem, the PTP communication schemes have been proposed but they are insufficient to generalize because they lack specific verification. In this paper, problems of an existed location estimation algorithm based on PTP communication are analyzed, and we propose a location estimation algorithm of a fixed object that satisfyies the condition of a single receiver being substituted to multiple receivers. A location estimation system we designed and implemented using CSS wireless communication modules to evaluate the proposed algorithm. We verify, by experimental results, that the optimum moving interval for the location estimation is 3m in indoor environment of $10m{\times}16m{\times}1m$.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.358-367
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• 2016

SSL (Sound Source Localization) has been applied to several applications such as man-machine interface, video conference system, smart car and so on. But in the process of sound source localization, angle estimation error is occurred mainly due to the non-linear characteristics of the sine inverse function. So an approach was proposed to decrease the effect of this non-linear characteristics, which divides the microphone's covering space into narrow regions. In this paper, we proposed an optimal space dividing way according to the pattern of microphone array. In addition, sound source's 2-dimensional position is estimated in order to evaluate the performance of this dividing method. In the experiment, GCC-PHAT (Generalized Cross Correlation PHAse Transform) method that is known to be robust with noisy environments is adopted and triangular pattern of 3 microphones and rectangular pattern of 4 microphones are tested with 100 speech data respectively. The experimental results show that triangular pattern can't estimate the correct position due to the lower space area resolution, but performance of rectangular pattern is dramatically improved with correct estimation rate of 67 %.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.55-63
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• 2013

In cognitive radio networks, acquirement of position information of primary user is very important to secondary network since localization information of primary users can be utilized for improving the spectrum efficiency of secondary network and for avoiding harmful interference to primary users by using proper power control. Among various location methods, Received Signal Strength (RSS)-based localization has been widely used for distance measurements in the location detection process despite its inherent inaccuracy because it can be easily implemented without any additional hardware cost. In the RSS-based localization, the distance is measured by the received signal strength, and distance error can be caused by many factors such as fading, shadowing and obstacle between two nodes. In the paper, therefore we propose a localization scheme based on estimation of path-loss exponent to localize the location of primary users more accurately. Through simulations, it is shown that the proposed scheme can provide less localization error and interference rate to primary users than other schemes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.218-226
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• 2020

An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.