• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.311-314
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• 2003

This paper describes a virtual instrument system with faulty sensor reconstruction mechanism based on personal computer. This system consists of sensor control board using 16bit RISC machine, error signal reconstruction algorithm based on principal component analysis and auto tunned GUI interface according to the attached sensors. USB module is used for fast communication between PC and sensor controller. To show the veridity of the proposed system, the proposed system was applied to the developed sun tracker with 8 solar sensors.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.314-320
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• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.19.2-19.2
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• 2005

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.643-651
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• 2015

Multi-axis magnetic and accelerometer sensor are widely used in consumer product such as smart phones. The vector output of multi-axis sensors have errors on each axis such as offset error, scale error, non-orthogonality. These errors cause many problems on the performance of the applications. In this paper, we designed the effective inline compensation algorithm for calibrating of 3 axis sensors using ellipsoid for mass production of multi-axis sensors. The outputs with those kinds of errors can be modeled by ellipsoid, and the proposed algorithm makes sequential mappings of the virtual ellipsoid to perfect sphere which is calibrated function of the sensor on three-dimensional space. The proposed calibrating process composed of four main stages and is very straightforward and effective. In addition, another imperfection of the sensor such as the drift from temperature can be easily inserted in each mapping stage. Numerical simulation and experimental results shows great performance of the proposed compensation algorithm.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.1140-1141
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• 2017

Depth of SWASH(Small Waterplane Area Single Hull) vessel which is an input value of its control system is measured by ultrasonic sensor. Distance to the its center of gravity can be simply calculated through ultrasonic sensor attached to the front of the vessel from the known values. However, it is to be calibrated with respect to its position for the accurate depth because it has geometric relation between the measurement value of ultrasonic sensor and the depth. In this research, depth calibration method of SWASH vessel using its position and ultrasonic sensor is introduced.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.493-495
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• 2015

PDR은 일반적으로 IMU센서로 부터의 가속도와 각속도를 측정하여 보행자의 위치를 추적하는 시스템이다. IMU센서로부터 측정된 가속도와 각속도 값은 센서를 기준으로 하기 때문에 보행자가 인지하는 고정 좌표계와는 차이가 있다. 이를 해결하기 위해 회전행렬을 사용하며 이후 계속해서 측정되는 각속도를 통해 회전행렬을 업데이트 한다. 업데이트된 회전행렬을 통해 좌표계를 환산하고 환산된 좌표계의 가속도 값으로부터 보행자는 고정좌표계 기준으로 위치 추적이 가능하다. 하지만 회전행렬을 업데이트 하는 과정에서 센서의 세 축이 이상적으로 수직이 아니라면 업데이트 과정에서 각속도의 오차가 누적되고 이는 좌표계를 환산에 영향을 끼쳐 위치 및 속도 추적 정확성을 낮춘다. 물리적인 Bias가 PDR 시스템에 누적오차를 발생시킨다. 이에 제안하는 센서 축 편향 보정 알고리즘은 IMU 센서의 물리적 축 오차를 보정해주어 더 정확한 위치 추적을 가능하게 한다. 또한 Matlab을 통해 데이터를 분석하고 알고리즘의 필요성을 보인다.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.35-43
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• 2012

In general, load carrying capacity, one of the load & resistance capacities in bridges, has more margins than the load carrying capacity evaluated with theoretical methods, unless there are severe damages, defects or material deterioration phenomena that can have a great impact on the behavior of bridges. However, errors have been already included in the current processes of loading tests and structural analysis for measuring load carrying capacity, thus devaluing the reliability of response adjustment factor. Therefore, this study found out the problems of existing electric resistance strain and displacement sensors in sensor suite to solve the problems with sensors and the errors in the appropriateness of structural analysis model, thereby leading to the changes into an optical fiber smart sensor with excellent performance. Besides, the study attempted to ensure the accuracy of response adjustment factor by selecting the optimal models through the interpretation of various structural analysis models.

• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.285-294
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• 2006

A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigated three sensor models: collinearity model, direct linear transform (DLT) model and orbit-based model. We applied matching between GOES images and global coastline database and used successful results as control points. With control points we improved the initial image geolocation accuracy using the three models. We compared results from three sensor models. As a result, we showed that the orbit-based model is a suitable sensor model for precise geolocation of GOES-9 Images.

• Proceedings of the Optical Society of Korea Conference
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• 2002.07a
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• pp.28-29
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• 2002

하트만 센서를 이용한 파면 왜곡 측정에서 측정 정밀도와 측정 속도는 왜곡을 실시간으로 보정하고자 하는 적응광학 기술에서 중요한 요소이다. 파면왜곡을 측정하고 보정하는 실제 환경에서 적응광학장치는 전기적으로 안정된 시스템의 구성이 요구된다. 본 논문에서는 하트만 센서를 이용한 파면 측정과정에서 넓은 측정 범위를 가지면서도 고속 정밀한 파면 정보를 추출할 수 있는 알고리즘을 연구하였고 적응광학 부품들을 제어함에 있어 전기적으로 안정된 하드웨어 장치들을 구성하였다. (중략)