• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1056-1061
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• 2009

This paper proposes a short-term water demand forecasting algorithm based on kalman filtering with data mining for sustainable water supply and effective energy saving. The proposed algorithm utilizes a mining method of water supply data and a decision tree method with special days like Chuseok. And the parameters of MLAR (Multi Linear Auto Regression) model are estimated by Kalman filtering algorithm. Thus, we can achieve the practicality of the proposed forecasting algorithm through the good results applied to actual operation data.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.672-675
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• 2009

BMS(Bus Management System)의 핵심인 버스도착예정시간을 산출하는 데 있어서 기존 대부분의 도시에서는 시계열 모형의 이동평균법, 칼만필터링 등으로 버스도착예정시간을 예측하고 있으나 이는 급격한 통행량의 변화 또는 급작스러운 사고, 신호체계 등에 적응 할 수 없다. 따라서 본 논문에서는 주변 도로의 통행량에 따른 버스의 정류장 도착시간을 예측하는 방법을 제안 한다. 주변 도로의 통행량과 실제 버스의 통행시간을 실측하여 기록, 학습하고 모델링하여 미래의 버스의 운행시간을 예측하는 방법이다. 또, 이동평균법에 의한 버스도착시간 예측결과와 본 논문에서 제안하는 결과와 비교, 분석하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.724-733
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• 2017

Accidents caused by upset condition leads to fatal damage to both manned and unmanned aircraft. This paper deals with real-time detection of these aircraft upset situations to prevent further severe situations. Firstly, the difference between sensor measurement and predicted measurement from Extended Kalman filter is monitored to determine whether a target aircraft goes into an upset condition or not. In addition, repeating the time update stage of the Extended Kalman filter for a specific length of time can enable future upset situation prediction. The results of aforementioned both the approaches will build a bridge to upset prevention for future generation of manned/unmanned aircraft.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.755-765
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• 2013

This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.51-59
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• 2005

To improve the quality of bus service, providing bus ravel time information to passenger through station screen. Generally, bus travel time information predict by using previous bus data such as neural network, Kalman filtering, and moving average algorithms. However, when they got a difficulty about bus travel time information because of the missing previous bus data, they use pattern data. Generally, nevertheless the difference of range is big. Hence in this research to calculate the bus travel time information when the bus information is missed, use queue detector's data which set up in link. The application of several factors which influence in bus link travel time, we used CORSIM Version 5.1 simulation package.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.43-48
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• 2012

This paper proposes a practical linear recursive robust motion deblurring filter using the inertial sensor measurements for strapdown image seekers. The angular rate information obtained from the gyro mounted on the missile is used to define the PSF(point spread function). Since the gyro output contains a unknown but bounded bias error. the motion blur image model can be expressed as the linear uncertain system. In consequence, the motion deblurring problem can be cast into the robust Kalman filtering which provides reliable state estimates even in the presence of the parametric uncertainty due to the gyro bias. Through the computer simulations using the actual IR scenes, it is verified that the proposed algorithm guarantees the robust motion deblurring performance.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.307-312
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• 2015

ARPA(Automatic Radar Plotting Aid) is a device to calculate CPA(closest point of approach)/TCPA(time of CPA), true course and speed of targets by vector operation of relative courses and speeds. The purpose of this study is to develop target acquisition and tracking technology for ARPA Radar implementation. After examining the previous studies, applicable algorithms and technologies were developed to be combined and basic ARPA functions were developed as a result. As for main research contents, the sequential image processing technology such as combination of grayscale conversion, gaussian smoothing, binary image conversion and labeling was deviced to achieve a proper target acquisition, and the NNS(Nearest Neighbor Search) algorithm was appllied to identify which target came from the previous image and finally Kalman Filter was used to calculate true course and speed of targets as an analysis of target behavior. Also all technologies stated above were implemented as a SW program and installed onboard, and verified the basic ARPA functions to be operable in practical use through onboard test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.125-132
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• 2015

This paper is about analysis of UDRE monitoring method for Korean Satellite navigation system, which is the correction parameter of satellite measurements. New receiver clock bias and tropospheric delay error estimation method to make pseudo-range residual for UDRE monitoring is proposed. Saastamoinen model and Neill mapping function are used for estimate the tropospheric delay and EKF is used for estimgate the receiver clock bias. Through the satellite measurements and regional weather data received directly from the domestic is using for UDRE monitoring analysis, more suitable UDRE monitoring threshold can be deducted and it is expected to be utilized for fault detection technique of Korean Satellite Navigation System.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.4
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• pp.292-299
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• 2012

The line-of-sight(LOS) rate is estimated using Kalman filter in Radio-Frequency(RF) seeker. For the two axis gimbaled seeker, proper system modeling is considered and the basic filter structure is set up. The main issue for Kalman filter is choosing the proper process and measurement noise. For the measurement process, the signal to noise ratio(SNR) and other components are introduced. To cope with the eclipse problem or other abnormal seeker status, the pseudo input signal concept is proposed. By conditioning abnormal signals, the LOS rate estimation performance is increased. The process noise is also an important factor in the propagation phase. The analytical approach on a process noise component is performed and a reliable region for the filter is calculated based on the eigenvalue analysis. Some numerical simulations are performed to check the validity of suggested algorithm.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.