• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.65-72
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• 2010

In this study, the performances of a medium grade IMU which is aimed for Mobile Mapping System and a low grade IMU for pedestrian navigation are analyzed through simulations under GPS signal blockage. In addition, an analysis on the accuracy improvement of barometer, electronic compass, or multi-sensor(combination of barometer and electronic compass) to correct medium grade or low grade IMU errors in the situation of GPS signal blockage is performed. With the medium grade IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 5m when the block time is over 30 seconds. When we correct IMU with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 60 seconds. In addition, barometer is more effective than the electronic compass when they are combined. In case of low grade IMU like MEMS IMU, the three dimensional positioning error from INS exceeds the demanded accuracy of 20m when the block time is over 15 seconds. When we correct INS with barometer, compass, or multi-sensor, however, the demanded accuracy is maintained up to 15 seconds in simulation results. On the contrary to medium grade IMU, electronic compass is more effective than the barometer in case of low velocity such as pedestrian navigation. It is expected that the analysis suggested a method to decrease position or attitude error using aided sensor integration when MMS or pedestrian navigation is operated under 1he environment of GPS signal blockage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.610-615
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• 2016

Diverse accessories are used in automobiles, such as navigation systems, front and rear cameras, spoilers, and sun visors. Sun visors block sunlight so that drivers can drive safely with a better view, and they are used in many automobile designs. However, when large plastic products are manufactured using injection molding, there are many difficulties that develop, like weld lines, short shots, flow marks, imperfections, and distortion. In this study, a CAE simulation was conducted based on previous results to predict potential problems in the injection molding of large products. The flow characteristics up to complete charge for the melting resins were captured using a computer-aided engineering simulation. The temperature departure on the front part of a flow was about $10^{\circ}C$ and very stable. The practical ejecting time of the cold runner was about 70 seconds in the simulation. Finally, the capability of a suitable injection machine was calculated and recommended by prediction of the injection pressure and the die clamping force.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.10
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• pp.1002-1009
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• 2009

Precision guidance filter design for a tactical missile with a strapdown seeker aided by low-cost strapdown sensors has been addressed in this paper. The low-cost strapdown sensors consist of an IMU with 3-axis accelerometers and gyroscopes, 3-axis magnetometers, and a barometer. Missile's position, velocity, attitude, and bias error of the barometer are considered as state variables. Since the state and measurement equations are highly nonlinear, we adopt UKF(Unscented Kalman Filter). The proposed guidance filter has a function of a navigation filter if target position error is not considered. In the case that the target position error is introduced, the proposed filter can effectively estimate the relative states of the missile to the true target. For specific engagement scenarios, we can observe that observability problems occur.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.630-637
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• 2019

The scientific, economical and industrial values of the Moon have been increased, as massive ice-water and rare resource were founded from the lunar exploration missions. Korea and other major space agencies in the world are competitively developing the ISRU (In Situ Resource Utilization) technology to secure future lunar resource as well as to construct the lunar base. To prepare for the lunar construction, it is essential to develop the rover based construction spatial information technology to provide a decision-making aided information during the lunar construction process. Thus, this research presented the construction spatial information technology based upon rover's camera system. Specifically, the conceptual design of rover based camera system was designed for acquisition of a rover's navigation image, and lunar terrain and construction images around the rover. The reference architecture of the rover operation system was designed for computation of the lunar construction spatial information. Also, rover's localization and terrain reconstruction methods were introduced considering the characteristics of lunar surface environments. It is necessary to test and validate the conceptual design of the construction spatial information technology. Thus, in the future study, the developed rover and rover operation system will be applied to the lunar terrestrial analogue site for further improvements.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.101-108
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• 2024

Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.