• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2195-2202
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• 2011

Recently, navigation system is used to inform users of vehicle location and driving direction, moving distance and so on. This navigation uses GPS sensor for current location determination. The GPS sensor will determinate current coordinates by using triangulation algorithm. This characteristic bring about that the GPS signal is not available in the shadow region such as tunnel and urban canyon. Moreover, Even though the signal is available, inherent positional error rate of the GPS often results in the dislocation of vehicle. To solve, these problems, a new positioning system is proposed in the paper. The System utilizes geomagnetic sensors of smartphone, speed information of CAN of vehicle though bluetooth and WiFi APs for GPS shadow area. The experimental test shadows that the proposed system using multiple data is able to determine the position of vehicle in GPS shadow areas.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.106-114
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• 2017

In this paper, we propose the method of designing an extended kalman filter in order to accurately measure the position of the spatial-phase system using sensor fusion. We use the quaternion as a state variable in expressing the attitude of an object. Then, the attitude of rigid body can be calculated from the accelerometer and magnetometer by applying the Gauss-Newton method. We estimate the changes of state by using the measurements obtained from the gyroscope, the quaternion, and the vision informations by ARVR_SDK. To increase the accuracy of estimation, we designed and implemented the extended kalman filter, which showed excellent ability to adjust and compensate the sensor error. As a result, we could experimentally demonstrate that the reliability of the attitude estimation value can be significantly increased.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.156-165
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• 2009

Threat due to malfunction of space launch vehicles is significant since it is bigger and flights longer range than military missiles or scientific rockets. It is necessary to implement a flight safety system to minimize the possible hazard. Design objective of the tracking filter for the flight safety system is different from conventional tracking filters since estimation reliability is more emphasized than estimation accuracy. In this paper, a fusion tracking filter was implemented for processing multi-sensor data from a space launch vehicle. The filter performance is evaluated by analyzing the error of the estimated position and instantaneous impact point. Also a fault detection algorithm is implemented to guarantee fusion filter's reliability under any sensor failure and verified to maintain stability successfully.

• Composites Research
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• v.34 no.3
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• pp.161-166
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• 2021

In this study, we present a research method to develop a shoe that prevents foot injury by inducing the foot pressure. An orthogonal grid sensor was used to check the foot pressure in the upright standing position, and the change in the foot pressure distribution for various conditions was compared. We checked the conditions for distributing foot pressure efficiently by changing the spring constant of the spring inserted into the sole of the shoe and the foot pressure generated with or without the arch of the insole. In order to minimize the experimental error from the randomness of the human body's behavior, it is possible to predict through foot pressure under certain conditions through finite element analysis that simulates the pressure distribution. By checking the change of foot pressure according to the number and arrangement of springs through finite element analysis, conditions were established to provide more efficient foot pressure. The result can be used for designing footwear for patients with diabetic feet.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Journal of Biomedical Engineering Research
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• v.41 no.2
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• pp.84-93
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• 2020

Despite of a lot of studies about proprioception tests, there are little study results to investigate the relationship between the functional movement and proprioception level. In this study, we tried to perform quantitative analysis for the effect of ankle joint proprioception level on the one leg standing postural control ability. Nine healthy people volunteered for this study. Force and position aspects of proprioception were evaluated using the electromyography system (EMG) and mobile clinometer application, respectively. The center of pressure (COP) trajectories, measured by a pressure mat sensor, were used for quantitative analysis of balance for each subject. We computed indices and errors of force and position aspects of proprioception from the EMG and ankle angle. Mean velocity of total and anterior-posterior direction (Vm and Vm_ap), root mean squared distance in anterior-posterior direction (RDap), travel length (L), and area (A) of COP trajectories were also calculated as indices of postural control ability of subjects. Two aspects of proprioception showed the low correlation from each other as previous studies. However, the EMG error of gastrocnemius lateral activation showed a high correlation coefficient with COP variables such as Vm (ρ=0.817, p=0.007), Vm_ap (ρ=0.883, p=0.002), RDap (ρ=0.854, p=0.003), L (ρ=0.817, 0.007) and A (ρ=0.700, p=0.036). Within our knowledge, this is almost the first study that investigated the relationship between proprioception level and functional movement. These study results could support that the ankle joint proprioception facilitation exercise would have positive effects on functional balance rehabilitation interventions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

When the sensor geometry is poor, the user position estimate obtained by of GN (Gauss-Newton) method is often diverged in radio navigation. In other to avoid divergence problem QCLS (Quadratic Correction Least Square) method using TDOA (Time Difference of Arrival) measurements is introduced, but the estimation error is somewhat large. This paper presents the modified QCLS method using weighted least square. Since the weighting matrix is influenced by the unknown user position, two-step approach is employed in the proposed method. The weighting matrix is estimated in the first step using least square, and then find user position is obtained using weighted least square. Simulation results show that the performance of the proposed method is superior to the conventional QCLS all over the workspace.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.486-492
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• 2015

Radiation source imaging system is essential for protecting of radiation leakage accidents and minimizing damages from the radioactive materials, and is expected to play an important role in the nuclear plant decommissioning area. In this study, the stereoscopic camera principle was applied to develop a new radiation imaging device technology that can extract the radiation three-dimensional position information. This radiation three-dimensional imaging device (K3-RIS) was designed as a compact structure consisting of a radiation sensor, a CCD camera, and a pan-tilt only. It features the acquisition of stereoscopic radiation images by position change control, high-resolution detection by continuous scan mode control, and stereoscopic image signal processing. The performance analysis test of K3-RIS was conducted for a gamma-ray source(Cs-137) in radiation calibration facility. The test result showed that a performance error with less than 3% regardless of distances of the objects.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1167-1175
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• 2010

This paper presents the use of the inertial measurement unit information and the infrared sector information for getting the position of an object. Travel distance is usually calculated from the double integration of the accelerometer output with respect to time; however, the accumulated errors due to the drift are inevitable. The orientation change of the accelerometer also causes error because the gravity is added to the measured acceleration. Unless three axis orientations are completely identified, the accelerometer alone does not provide correct acceleration for estimating the travel distance. We propose a way of minimizing the error due to the change of the orientation. In order to reduce the accumulated error, the infrared sector information is fused with the inertial measurement unit information. Infrared sector information has highly deterministic characteristics, different from RFID. By putting several infrared emitters on the ceiling, the floor is divided into many different sectors and each sector is set to have a unique identification. Infrared light based sector information tells the sector the object is in, but the size of the uncertainty is too large if only the sector information is used. This paper presents an algorithm which combines both the inertial measurement unit information and the sector information so that the size of the uncertainty becomes smaller. It also introduces a framework which can be used with other types of the artificial landmarks. The characteristics of the developed infrared light based sector and the proposed algorithm are verified from the experiments.

• Journal of IKEEE
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• v.17 no.4
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• pp.440-445
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• 2013

This paper proposes a local estimation system which combines Cell Divide Algorithm with low-cost GPS/INS fused by Extended Kalman Filter(EKF) for localization of Quad-rotor when it returns to the departure point. In the research, the low-cost GPS and INS are fused by EKF to reduce the local error of low-cost GPS and the accumulative error of INS due to continuous integration of sensor error values. When the Quad-rotor returns to the departure point in the fastest path, a moving path can be known because it moves straight, where Cell Divide Algorithm is used to divide moving route into the cells. Then it determines the closest position of data of GPS/INS system fused by EKF to obtain the improved local data. The proposed system was verified through comparing experimental localization results obtained by using GPS, GPS/INS and GPS/INS with Cell Divide Algorithm respectively.