• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1227-1230
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• 2003

In this paper, we propose a pose estimation method using local map acquired from 2d laser range finder information. The proposed method uses extended kalman filter. The state equation is a navigation system equation of Nomad Super Scout II. The measurement equation is a map-based measurement equation using a SICK PLS 101-112 sensor. We describe a map consisting of geometric features such as plane, edge and corner. For pose estimation we scan external environments by laser rage finer. And then these data are fed to kalman filter to estimate robot pose and position. The proposed method enables very fast simultaneous map building and pose estimation.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.45-50
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• 2001

The impact evaluation of a DSM program is a very important issue since the results are used to determine the sustainability of a program. In general. to estimate the impacts of a DSM program it is required to measure the electricity usage changes before and after a program. Since the measurement-based approaches cost highly, most of the conventional evaluations are based on the average figures. However estimation of the average-based impacts can lead to both distorted results of over/under estimation of kW and kWh savings and non-optimal DSM planning. In this paper, we have developed a new multi-point measurement approach which can evaluate kW and kWh savings of a DSM program more exactly. To do this, the saving rate and operating rate are defined and set as the function of load factor of a customer, and these rates are incorporated with the conventional diffusion function of Bass to project the future impacts of a DSM program. The case study is performed on the inverter program of Korea by using the suggested approach.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.3 s.246
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• pp.270-277
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• 2006

Inverse radiation problems were solved for estimating boundary temperature distribution in a way of function estimation approach in an axisymmetric absorbing, emitting and scattering medium, given the measured radiative data. In order to reduce the computational time fur the calculation of sensitivity matrix, automatic differentiation and Broyden combined method were adopted, and their computational precision and efficiency were compared with the result obtained by finite difference approximation.. In inverse analysis, the effects of the precision of sensitivity matrix, the number of measurement points and measurement error on the estimation accuracy had been inspected using quasi-Newton method as an inverse method. Inverse solutions were validated with the result acquired by additional inverse methods of conjugate-gradient method or Levenberg-Marquardt method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1791-1797
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• 2014

A water level measurement radar estimates beat frequencies to extract the corresponding water level information for water resource management. Therefore, it is required to maintain the high degree of reliability and accuracy in beat frequency estimates. However, Beat spectra of water surface return echoes can have very widely varying shapes according to system frequency linearity, measurement environments and weather conditions. Therefore, serious problems may arise in maintaining the reliability and accuracy of the conventional level estimation method. Therefore, in this paper, high resolution spectrum estimates are analyzed for improvement of the conventional method. These methods show that the more accurate level measurement can be possible on the condition that SNR is higher than a certain required threshold. However, if SNR is too low, the conventional method shows that estimates are more reliable than the suggested method though absolute errors are too large.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.265-274
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• 2019

The paper describes an application of unscented Kalman filter(UKF) for attitude estimation of an unmanned vehicle(UV), which is equipped with a low-cost attitude heading reference system (AHRS). The roll, pitch and yaw required at the correction stage of the UKF are calculated from the measurements of acceleration and geomagnetic field. The roll and pitch are attributed to the measurement of acceleration, while yaw is calculated from the geomagnetic field measurement. Since the measurement of geomagnetic field is vulnerable to distortion by hard-iron and soft-iron effects, the calculated yaw has more uncertainty than the calculated roll and pitch. To reduce the uncertainty of geomagnetic field measurement, the proposed method estimates bias in the geomagnetic field measurement and compensates for the bias for more accurate calculation of yaw. The proposed method is verified through navigation experiments of a UV in a test pool. The results show that the proposed method yields more accurate attitude estimation; thus, it results more accurate location estimation.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.69-71
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• 2010

In this paper, we focus on the accuracy estimation of laser scanning mobile mapping system using Lynx Mobile Mapper. For this, we surveyed checkpoints(181 points) in study areas. A method to estimate the accuracy of laser scanning mobile mapping system based on the measurement range, interval of control points and gps signal environments. As a result, to ensure reliable measurement results, we must be made a plan considering Measure range(60m or under) and operation. The estimation results showed the need for improving accuracy using control points about 150m interval according to environment error source.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.419-427
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• 2020

In this study, a particle image velocimetry (PIV)-based pressure estimation method was investigated, with application to the wave-in-deck loading phenomenon. An experimental study was performed in a two-dimensional wave tank using a fixed deck structure under a focused wave, obtaining local pressures by pressure sensors, global loads by load cells, and instantaneous velocity fields using the PIV measurement technique. The PIV-based pressure estimation method was applied using the Euler equation as the governing equation, and the proper time step for the wave impact pressure was studied using the normalized root-mean-square deviation. The pressure estimation method showed good agreement for the local impact pressure in comparison with the measured pressure by the pressure sensors. However, some differences were observed in the peak pressure due to the limitations of the Euler equation and the sampling rate of the measurement system. Using the estimation method, the pressure fields during wave-in-deck loading were determined in the study, with an analysis of the mechanism of impact and negative pressure occurrence.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.529-530
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• 2007

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using PSO. This PSO-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using PSO in the HSE.

• Journal of Sensor Science and Technology
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• v.28 no.2
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• pp.81-87
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• 2019

One of the major issues in inertial and magnetic measurement unit (IMMU)-based 3D orientation estimation is compensation for magnetic disturbances in magnetometer signals, as the magnetic disturbance is a major cause of inaccurate yaw estimation. In the proposed approach, a kinematic constraint is used to provide a measurement equation in addition to the accelerometer and magnetometer signals to mitigate the disturbance effect on the orientation estimation. Although a Kalman filter (KF) is the most popular framework for IMMU-based orientation estimation, a complementary filter (CF) has its own advantages over KF in terms of mathematical simplicity and ease of implementation. Accordingly, this paper introduces a quaternion-based CF with a constraint-combined correction equation. Furthermore, the weight of the constraint relative to the magnetometer signal is adjusted to adapt to magnetic environments to optimally deal with the magnetic disturbance. In the results of our validation experiments, the average and maximum of yaw errors were $1.17^{\circ}$ and $1.65^{\circ}$ from the proposed CF, respectively, and $8.88^{\circ}$ and $14.73^{\circ}$ from the conventional CF, respectively, showing the superiority of the proposed approach.