• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.217-219
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• 2010

Sensor modeling is the basic step to extract and to use the information from satellite images. Sensor modeling requires ground control points. If we use a single image, we have limitations on modeling about images captured from regions that we can not approach or take GCPs. In this research, we use strip images to do sensor modeling by two methods. At first, we apply sensor modeiling to single image and apply the results by extrapolation. Next, we consider strip images to single image. As a result, we find the second method is more accurate about whole image.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.112-116
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• 2008

This paper presents URS (Ubiquitous Robotic Space) Modeling and service technique for the robotic security service while bridging between virtual space and physical space. First, this paper introduces a concept of virtual URS and responsive virtual URS. Second, this paper addresses modeling of URS which covers modeling of indoor geometry and environment sensor. Third, this paper describes virtual URS services including interactive virual-physical bridging service.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.217-220
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• 2005

Currently, a number of control points are required in order to achieve accurate geolocation of satellite images. Control points can be generated from existing maps or surveying, or, preferably, from GPS measurements. The requirement of control points increase the cost of satellite mapping, let alone it makes the mapping over inaccessible areas troublesome. This paper investigates the possibilities of modeling an entire imaging strip with control points obtained from a small portion of the strip. We tested physical sensor models that were based on satellite orbit and attitude angles. It was anticipated that orbit modeling needed a sensor model with good accuracy of exterior orientation estimation, rather then the accuracy of bundle adjustment. We implemented sensor models with various parameter sets and checked their accuracy when applied to the scenes on the same orbital strip together with the bundle adjustment accuracy and the accuracy of estimated exterior orientation parameters. Results showed that although the models with good bundle adjustments accuracy did not always good orbit modeling and that the models with simple unknowns could be used for orbit modeling.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.475-480
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• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.207-212
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• 2008

There are several sensors in the liquid cargo ship. In the liquid cargo ship, we can get values from various sensors that are level sensor, temperature sensor, pressure sensor, oxygen sensor, VOCs sensor, high overfill sensor, etc. It is important to guarantee the reliability of sensors. In order to guarantee the reliability of sensors, we have to study the diagnosis of sensor fault. The technology of smart sensor is widely used. In this paper, the technology of smart sensor is applied to diagnosis of level sensor fault for liquid cargo ship. In order to diagnose sensor fault and find the sensor position, in this paper, we proposed algorithms of diagnosis of sensor fault using independent sensor diagnosis unit and self fault diagnosis using sensor modeling. Proposed methods are demonstrated by experiment and simulation. The results show that the proposed approach is useful. Proposed methods are useful to develop smart level sensor.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.27-33
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• 2016

In this study we propose a method for 3D landform reconstruction and object modeling method by generating contour lines on the map using a depth sensor which abstracts characteristics of geological layers from the depth map. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust contour and object can be extracted. The algorithm suggested in this paper first abstracts the characteristics of each geological layer from the depth map image and rearranges it into the proper order, then creates contour lines using the Bezier curve. Using the created contour lines, 3D images are reconstructed through rendering by mapping RGB images of the visual camera. Experimental results show that the proposed method using depth sensor can reconstruct contour map and 3D modeling in real-time. The generation of the contours with depth data is more efficient and economical in terms of the quality and accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.71-78
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• 2006

Sun sensors are frequently implemented by satellites for attitude sensing, due to its simple manufacturability and light weight. A modeling of sun sensors has an important effect on the accuracy of satellite attitude determination. This paper addresses a new modeling of a 2-axis miniature fine sun sensor with improved accuracy. Unlike other previous algebraic modeling methods, the newly suggested physical modeling method takes into account the shadowing effect of the slit thickness. It was shown that a newly proposed sun sensor modeling provides a substantial accuracy improvement of 29% compared to the generic algebraic modeling. The proposed sensor modeling was validated using 2-axis fine sun sensors with FOV(Field of View) of ${\pm}60^{\circ}$ mounted on HAUSAT-2 small satellite, currently under development by SSRL(Space System Research Lab.) at Hankuk Aviation University, Korea.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.177-182
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• 2004

In sonar sensor design impedance matching design to each sensor affects the whole weighting circuit characteristic very much. But there are many examples that it is made by hands or very simple modeling designs. So these design works make trial and error because it is the limitation of flexible correspondence to the many sensors and follows many errors. This study explains organizations and skills in the sensor modeling package design program with real sonar sensor characteristic measure as the first step in impedance matching design.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.179-184
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• 2005

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior, and so on, in the robot, is hard and need to make efforts to use our originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various Points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.