• 한국자동차공학회논문집
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• 제12권6호
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• pp.182-190
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• 2004

This paper presents reconstruction analysis of vehicle trajectory using records of a developed black box, and results of validation tests. For reconstruction of vehicle trajectory, the black box records the longitudinal and lateral accelerations and yaw-rate of vehicle during a pre-defined time period before and after the accident. One 2-axis accelerometer is used for measuring accelerations, and one vibrating structure type gyroscope is used for measuring yaw-rate of vehicle. The vehicle's planar trajectory can be reconstructed by integrating twice accelerations along longitudinal and lateral directions with yaw-rate values. However, there may be many kinds of errors in sensor measurements. The causes of errors are as follows: mis-alignment, low frequency offset drift, high frequency noise, and projecting 3-dimensional motion into 2-dimensional motion. Therefore, some procedures are taken for error compensation. In order to evaluate the reliability and the accuracy of trajectory reconstruction results, the black box was mounted on a passenger car. The vehicle was driven and tested along various specified lanes. Through the tests, the accuracy and usefulness of the reconstruction analysis have been validated.

• 제어로봇시스템학회논문지
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• 제18권11호
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• pp.1065-1071
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• 2012

In this paper, we proposed a method for vehicle monitoring with trajectory reconstruction. For safety, it is important to monitor the driving habit of driver. Every year, many accidents occur due to the reckless driving of the driver. Continuous monitoring of the status of commercial vehicles is needed for safety through the entire path from start point to the destination. To monitor the reckless driving, we try to monitor the trajectory of the vehicle by using vehicle's lateral acceleration data. Compared with steering angle and lateral acceleration, these resemble each other. So, we find the relationship of steering angle and acceleration, and find the global direction of vehicle. We find the position of non-GPS section with EKF (External Kalman Filter) and reconstruct the whole trajectory during vehicle driving.

• Investigative Magnetic Resonance Imaging
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• 제13권1호
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• pp.15-21
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• 2009

목적 : 나선 주사 영상에서 경사자계시스템의 회로 모델을 기반으로 실제 경사 자계를 추정하여 재구성에 사용함으로써 재구성 영상을 개선하는 방법을 제안하였다. 대상 및 방법 : 자기공명영상장치의 경사자계 시스템은 저항 성분과 자체 인덕턴스, magnet 시스템과의 상호 인덕턴스, 커패시턴스 성분 등을 가지고 있어서 경사자계 증폭기에 인가하는 입력 경사자계 파형과 실제 만들어지는 경사자계 사이에는 시간적인 지연과 함께 파형에도 차이가 있다. 나선주사 영상에서 실제 만들어진 경사자계 파형 및 k-space 궤적은 재구성 과정에서 매우 중요한 역할을 한다. 본 논문에서는 경사자계시스템을 회로 소자로 모델링하였고, 입력 전압 파형에 대한 출력 전류 파형을 구함으로써 실제 얻어지는 경사자계파형을 유도하였다. 모델링에서 사용한 R-L-C 값은 재구성영상의 화질로부터 얻을 수 있는 방법을 제시하였다. 결과 : 1.5 Tesla MRI 시스템에서 경사자계 시스템의 입력 전압 파형에 대하여 실제 얻어지는 경사자계 파형을 추정할 수 있었다. 경사자계파형을 적분함으로써 얻어진 나선 궤적을 재구성에 적용한 결과 재구성 영상의 균일도가 개선되었고, edge 부근에서 overshoot 가 줄어들었으며, 해상도가 향상된 영상을 얻을 수 있었다. 결론 : R-L-C 회로 모델을 이용하여 경사자계시스템을 성공적으로 모델링할 수 있었고, 입력 전압 파형에 대하여 실제 얻어지는 경사자계(전류) 파형을 추정할 수 있었다. 이로부터 얻은 kspace 나선 궤적을 이용하여 월등히 개선된 재구성영상을 얻을 수 있었다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.157-160
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• 1996

In this paper, reconstruction algorithms of spiral scan imaging which has been used for ultra fast magnetic resonance imaging have been reviewed, and some simulation results using two different algorithms are reported. Since the trajectory of the spiral scan in k-space is the spiral, reconstruction of the spiral scan is not as straight forward as that used in Fourier imaging technique where the sampling points are usually on the rectangular grids. Originally the reconstruction of the spiral scan imaging was based on the convolution backprojection algorithm modified with a shift term, however, some other reconstruction techniques have also been tried by remapping sampling points from spiral trajectory to Cartesian grids. Some experimental aspects of MR spiral scan imaging will also be addressed.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.94-102
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• 2023

Anomaly detection in human movements can improve safety in indoor workplaces. In this paper, we design a framework for detecting anomalous trajectories of humans in indoor spaces based on a variational autoencoder (VAE) with Bi-LSTM layers. First, the VAE is trained to capture the latent representation of normal trajectories. Then the abnormality of a new trajectory is checked using the trained VAE. In this step, the anomaly score of the trajectory is determined using the trajectory reconstruction error through the VAE. If the anomaly score exceeds a threshold, the trajectory is detected as an anomaly. To select the anomaly threshold, a new metric called D-score is proposed, which measures the difference between recall and precision. The anomaly threshold is selected according to the minimum value of the D-score on the validation set. The MIT Badge dataset, which is a real trajectory dataset of workers in indoor space, is used to evaluate the proposed framework. The experiment results show that our framework effectively identifies abnormal trajectories with 81.22% in terms of the F1-score.

• Investigative Magnetic Resonance Imaging
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• 제25권4호
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• pp.293-299
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• 2021

Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

• 전자공학회논문지B
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• 제30B권4호
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• pp.67-75
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• 1993

The Fourier series are employed to approximate the input/output(I/O) characteristics of a dynamic system and, based on the approximation, a new learing control algorithm is proposed in order to find iteratively the control input for tracking a desired trajectory. The use of the Fourier approximation of I/O renders at least a couple of useful consequences: the frequency characteristics of the system can be used in the controller design and the reconstruction of the system states is not required. The convergence condition of the proposed algorithm is provided and the existence and uniqueness of the desired control input is discussed. The effectiveness of the proposed algorithm is illustrated by computer simulation for a robot trajectory tracking. It is shown that, by adding feedback term in learning control algorithm, robustness and convergence speed can be improved.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.205-207
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• 2004

The simple method of the geometric reconstruction of satellite linear pushbroom images is investigated. The model of the sensor used is based on the SPOT model that is developed by Kraiky. The satellite trajectory is a Keplerian trajectory in the approximation. Four orbital parameters, longitude of the ascending $node(\omega),$ inclination of the orbit plan(I), latitude argument of the satellite(W) and distance between earth center and satellite, are used for the camera modeling. We suppose that four orbital parameters and satellite attitude angles are exactly acquired. Then, in order to refine model, the given attitude angles and orbital parameters is not changed, but time-independent four parameters associated with LOS(Line Of Sight) vector is updated. A pair of SPOT-5 images has been used for validation of proposed method. Two GCPs acquired by GPS survey is used to controlling the LOS vector. The results are that the RMSE of 16 checking points are about 4.5m. Because the ground resolution of SPOT-5 is 2.5m, the result obtained in this study has a good accuracy. It demonstrates that the sensor model developed by this study can be used to reconstruct the geometry of satellite image taken by pushbroom camera.

• 한국항공우주학회지
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• 제44권6호
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• pp.502-511
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• 2016

최근 다양한 형태와 기능을 갖춘 스마트 무기들이 개발되고 있다. 화포탄의 경우 스마트 탄을 개발하기 위한 초기 연구로 신관 내부에 GNSS 수신기를 장착하여 탄자의 비행위치를 정밀하게 측정하고 이를 바탕으로 탄착점을 추정하는 연구가 진행되고 있다. 하지만, 수신기 성능 및 수신된 데이터에 포함된 다양한 오차유발 원인들로 인해 항법데이터의 위치정확도에 오차가 발생하게 된다. 본 논문에서는 PRODAS로부터 얻은 모의궤적 데이터를 수신기로부터 얻은 항법데이터에 포함된 PDOP 가중치를 적용하여 정합함으로써 탄의 발사부터 탄착까지의 전체 비행궤적 및 탄착점을 보다 정밀하게 추정하는 개선된 알고리즘을 소개한다.

• 한국자동차공학회논문집
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• 제13권4호
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• pp.8-18
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• 2005

Pedestrians involved in traffic accidents manifest unique trajectory characteristics depending on the collision speed, vehicle configuration, and pedestrian postures. However, the existing analytical models for pedestrian movements do not fully include the rotational characteristics of the pedestrians because they assume a two dimensional parabolic trajectory. This faulty assumption in the development of these models limits their applicability and reliability This study investigated the pedestrians movement at collision by computer simulation. The simulations are carried out by using HADYMO, which is a special simulation software system for dynamic movement analysis. Vehicles and pedestrians are modeled and verified via real crash worthiness experiments. Simulations are performed for various collision speeds, vehicle configuration, and pedestrian postures. Since the simulation uses multi-body dynamics, It can express irregular phenomena of the bodies quite well. The results can be exploited for vehicle design and traffic accident reconstruction.