• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.220-227
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• 2018

The most widely used method for constructing an inertial navigation system (INS)/global navigation satellite system (GNSS) coupling system is to construct an integrated navigation system using a Kalman filter. However, depending on the trajectory, non-observable state variables may be generated. In this case, the state variables are not estimated. To solve this problem, a integrated navigation system is constructed and then an observability analysis is performed. In this paper, a 24th order position-matched Kalman filter is defined to design an INS/GNSS integrated navigation system for vehicles moving with a large pitch angle change. To verify the appropriateness of the error state variables applied to the Kalman filter, an observability analysis was performed. The trajectory was divided into five segments, and the piece-wise constant system (PWCS) was assumed for each segment, and the results were analytically analyzed. The analytical results and the simulation results confirm that the error state parameters of the Kalman filter are well-designed to the estimation side.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.15-21
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• 2009

Purpose : A method to estimate a real k-space trajectory based on a circuit model of the gradient system is proposed for spiral imaging. The estimated k-space trajectory instead of the ideal trajectory is used in the reconstruction to improve the image quality in the spiral imaging. Materials and Methods : Since the gradient system has self resistance, capacitance, and inductance, as well as the mutual inductance between the magnet and the gradient coils, the generated gradient fields have delays and transient responses compared to the input waveform to the gradient system. The real gradient fields and their trajectory in k-space play an important role in the reconstruction. In this paper, the gradient system is modeled with R-L-C circuits, and real gradient fields are estimated from the input to the model. An experimental method to determine the model parameters (R, L, C values) is also suggested from the quality of the reconstructed image. Results : The gradient fields are estimated from the circuit model of the gradient system at 1.5 Tesla MRI system. The spiral trajectory obtained by the integration of the estimated gradient fields is used for the reconstruction. From experiments, the reconstructed images using the estimated trajectory show improved uniformity, reduced overshoots near the edges, and enhanced resolutions compared to those using the ideal trajectory without model. Conclusion : The gradient system was successfully modeled by the R-L-C circuits. Much improved reconstruction was achieved in the spiral imaging using the trajectory estimated by the proposed model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.261-262
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• 2012

In this research, intelligent protection system for laser boat is introduced. The function of system is to measure the distance and velocity of object from our boat and generate control signals to avoid collision with moving targets. A novel approach to estimate object's position from our ship is tackled on this paper. To do this laser sensors are used to measure distance from ship to targets. The ship position and velocity is estimated by th Kalman filter algorithm. In the real phase, the filtering method will be applied to process signal gathered by laser sensors. Simulation to estimate ship's position and velocity under noise are executed and the results are introduced to show the effectiveness of the algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.99-104
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• 2021

The technology of estimating a movement trajectory using a monocular camera such as a smartphone and composing a surrounding 3D image is key not only in indoor positioning but also in the metaverse service. The most important thing in this technique is to estimate the coordinates of the moving camera center. In this paper, a new algorithm for geometrically estimating the moving distance is proposed. The coordinates of the 3D object point are obtained from the first and second photos, and the movement distance vector is obtained using the matching feature points of the first and third photos. Then, while moving the coordinates of the origin of the third camera, a position where the 3D object point and the feature point of the third picture coincide is obtained. Its possibility and accuracy were verified by applying it to actual continuous image data.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.343-356
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• 2007

Due to advances in position monitoring technologies such as global positioning systems and sensor networks, recent position information of moving objects has the form of streaming data which are updated continuously and rapidly. In this paper we propose an efficient trajectory maintenance method that stores the streaming position data of moving objects in the limited size of storage space and estimates past positions based on the stored data. For this, we first propose a new concept of incremental extraction of position information. The incremental extraction means that, whenever a new position is added into the system, we incrementally re-compute the new version of past position data maintained in the system using the current version of past position data and the newly added position. Next, based on the incremental extraction, we present an overall framework that stores position information and estimates past positions in the stream environment. We then propose two polynomial-based methods, line-based and curve-based methods, as the method of estimating the past positions on the framework. We also propose three incremental extraction methods: equi-width, slope-based, and recent-emphasis extraction methods. Experimental results show that the proposed incremental extraction provides the relatively high accuracy (error rate is less than 3%) even though we maintain only a little portion (only 0.1%) of past position information. In particular, the curve-based incremental extraction provides very low error rate of 1.5% even storing 0.1% of total position data. These results indicate that our incremental extraction methods provide an efficient framework for storing the position information of moving objects and estimating the past positions in the stream environment.

• Journal of Biomedical Engineering Research
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• v.14 no.1
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• pp.1-8
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• 1993

In this study, the extractions of formants and articulatory motion trajectories for Korean complex vowels are performed by using the RLSL adaptive linear prediction filter. This enables us to extract accurate spectrum in transition of speech signal. This study shows that the RLSL algorithm is superior to the Levinson algorithm, specially in transition part of speech.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1231-1233
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• 1996

This paper presents an estimation of relative distance and angle from a mobile robot to an object. From the number of pulses required to make the mobile robot move to the feature point, we find the relative distance and angle between the mobile robot and the object. The proposed method shows a practical way of measuring the relative distance and angle between the mobile robot and an object without setting up real world coordinate system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.129-131
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• 2010

분산 비디오 부호화(distributed video coding)는 분산 소스 부호화의 대표적인 응용분야로서 부호화 복잡도가 부호화기에서 복호화기로 이동되어 저전력 부호화 환경에 매우 적합하다. 본 논문에서는 분산 비디오 부호화의 성능 향상에 있어 가장 중요한 보조 정보의 효과적인 생성 방법을 제안한다. 우선 보조 정보 생성을 위한 키 프레임들 간의 블록 움직임 추정에 있어 기존 방법들이 대체적으로 가정하고 있는 선형적인 움직임 이동에 따른 잘못된 예측을 해결하기 위해 두 장 이상의 키 프레임을 사용하여 블록 움직임을 추정한 후, 선형 회귀(linear regression)를 이용하여 보조 정보 상의 블록 움직임 궤적을 추정한다. 이때 움직임 추정을 위한 키 프레임 번호를 증가하며 선입선출(FIFO)형 버퍼에 저장 및 삭제하여 동일한 보조정보에 해당하는 여러 움직임 벡터 필드와, 기존의 선형적인 움직임이 가정된 움직임 벡터 필드를 동시에 생성한다. 다음으로 보간(interpolation)하려는 보조 정보 프레임 내의 임의의 블록에 가장 가깝게 통과하는 움직임 벡터 필드를 선택하여 해당하는 블록의 최종 움직임 벡터로 선택한다. 실험결과 제안하는 보조 정보 생성 방법은 기존의 방법과 비교했을 때 비대칭성 움직임 벡터 사용만으로 평균 PSNR이 0.216dB 만큼 증가하는 것을 확인할 수 있었다.

• Journal of Advanced Navigation Technology
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• v.6 no.2
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• pp.119-129
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• 2002

Maneuvering targets are difficult to track for the Kalman filter since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a highly maneuvering target, several schemes have been proposed and improved the tracking performance in some extent. Among those tracking schemes the Input Estimation (IE), Variable Dimension (VD) and Turning Acceleration Estimator (TAE) became popular. However, so far their tracking performances were analyzed individually and were not compared. In this paper, the tracking performances of the typical IE, VD and TAE schemes for a maneuvering target are compared. Monte-Carlo Simulations for three maneuvering profiles are carried out and the results are analyzed towards practical applications.

• Survey Research
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• v.11 no.1
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• pp.43-61
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• 2010

This research estimated the variation of high school students' academic achievement by using the second to the fourth wave KEEP(Korea Education and Employment Panel) data. We explored the effects of study on academic achievement in proportion to self-regulated learning hours(except for school work and private tutoring). Analysis variables were self-directed learning(study) hours throughout senior high school and 9 grade academic achievement. We conducted Latent Growth Model(LGM) using KEEP panel data and program LISREL 8.8. Results showed that there were significant effects of self-regulated learning hours on the variation of senior high school students' academic achievement. Therefore, this was considered to be useful tips in getting the relation between students' learning and academic achievement.