• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.12
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• pp.1115-1123
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• 2011

This paper proposes an image processing algorithms for detection and tracking of aerial vehicles in short-range. Proposed algorithm detects moving objects by using image homography calculated from consecutive video frames and determines whether the detected objects are approaching aerial vehicles by the Probabilistic Multi-Hypothesis Tracking method(PMHT). This algorithm can perform better than simple color-based detection methods since it can detect moving objects under complex background such as the ground seen during low altitude flight and consider the characteristics of vehicle dynamics. Furthermore, it is effective for the flight test due to the reduction of thresholding sensitivity against external factors. The performance of proposed algorithm is verified by applying to the onboard video obtained by flight test.

• Journal of Navigation and Port Research
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• v.42 no.2
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• pp.87-96
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• 2018

A trajectory control system plays an important role in controlling motions of marine vehicle when a series of way points or a path is given. In this paper, a sliding mode control (SMC)-based trajectory tracking controller for marine vehicles is presented. A small-sized unmanned ship is considered as a control object. Both speed and heading angle of a ship should be controlled for tracking control. The common point of related researches was to separate ship's speed and heading angle in control methods. In this research, a new control law from a general sliding mode theory that can be applied to MIMO (multi input multi output) system is derived and both speed and heading angle of a ship can be controlled simultaneously. The propulsion force and rudder force are also applied in modeling stage to achieve accurate simulation. Disturbance induced by wind is also tackled in the dynamics considering robustness of the proposed control scheme. In the simulation, we employed a way-point method to generate ship's trajectory and applied the proposed control scheme to ship's trajectory tracking control. Our results confirmed that the tracking error was converged to zero, thus demonstrating the effectiveness of the proposed method.

• Korean Journal of Artificial Intelligence
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• v.12 no.3
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• pp.1-7
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• 2024

In this paper, we propose an innovative super-resolution technique to address the issue of reduced accuracy in license plate recognition caused by low-resolution images. Conventional vehicle license plate recognition systems have relied on images obtained from fixed surveillance cameras for traffic detection to perform vehicle detection, tracking, and license plate recognition. However, during this process, image quality degradation occurred due to the physical distance between the camera and the vehicle, vehicle movement, and external environmental factors such as weather and lighting conditions. In particular, the acquisition of low-resolution images due to camera performance limitations has been a major cause of significantly reduced accuracy in license plate recognition. To solve this problem, we propose a Single Image Super-Resolution (SISR) model with a parallel structure that combines Multi-Scale and Attention Mechanism. This model is capable of effectively extracting features at various scales and focusing on important areas. Specifically, it generates feature maps of various sizes through a multi-branch structure and emphasizes the key features of license plates using an Attention Mechanism. Experimental results show that the proposed model demonstrates significantly improved recognition accuracy compared to existing vehicle license plate super-resolution methods using Bicubic Interpolation.

• 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.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.29-32
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• 1999

Korea Multi-Purpose SATellite(KOMPSAT) is scheduled to be launched by TAURUS launch vehicle in November, 1999. Tracking, Telemetry and Command(TT&C) operation and the flight dynamics support should be performed for the successful Launch and Early Orbit Phase(LEOP) operation. After the first contact of the KOMPSAT spacecraft, initial orbit determination using ground based tracking data should be performed for the acquisition of the orbit. Although the KOMPSAT is planned to be directly inserted into the Sun- synchronous orbit of 685 km altitude, the orbit maneuvers are required fur the correction of the launch vehicle dispersion. Flight dynamics support such as orbit determination and maneuver planning will be performed by using KOMPSAT Mission Analysis and Planning Subsystem(MAPS) in KOMPSAT Mission Control Element(MCE). The KOMPSAT MAPS have been jointly developed by Electronics and Telecommunications Research Institute(ETRI) and Hyundai Space & Aircraft Company(HYSA). The KOMPSAT MCE was installed in Korea Aerospace Research Institute(KARI) site for the KOMPSAT operation. In this paper, the orbit determination and maneuver planning are introduced and simulated for the KOMPSAT spacecraft in LEOP operation. Initial orbit determination using short arc tracking data and definitive orbit determination using multiple passes tracking data are performed. Orbit maneuvers for the altitude correction and inclination correction are planned for achieving the final mission orbit of the KOMPSAT.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.513-520
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• 2007

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.599-605
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• 2017

For an unmanned vehicle to be driven on the off-road terrain, it is necessary to consider the vehicle's stability. This paper suggests a path tracking controller for simulation of real-time vehicle stability analysis. The path tracking controller uses the preview distance to track the given trajectory. The disturbance moment is estimated using the yaw moment observer, and this information is used for compensation in the yaw moment control. On a curved path, the vehicle's desired velocity is determined from the curvature of the path. Because the vehicle is equipped with six independent motor driven wheels, the driving torques are distributed on all the wheels. The effectiveness of the path tracking controller is verified using ADAMS/MATLAB co-simulation.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.39-49
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• 2017

A Space Launch Vehicle (SLV) for Launching Satellites Consists of Multi-stage Rockets for the Purpose of Efficient Flight and Accomplishes the Launch Mission through Flight Events such as Stage Separation, Engine Start and Stop. In this Process, the SLV is Supposed to Undergo the Processes of the Powered Flight Section in which the Engine Generates Thrust and the Ballistic Flight Section in which there is no Thrust Repeatedly. Because it is Difficult to Express these Flight Characteristics of the SLV as a Single Dynamics Model, much Research on Tracking Algorithms using Multiple Models has been Undertaken. In case of using the Multiple Model Tracking Algorithm, it is Expected to Improve the Tracking Performance of the SLV. However, it is Difficult to Select Proper Dynamics Models to be used and the Calculation Amount Increases due to the use of Multiple Models. In this Paper, we Propose a Method to Track the SLV with Diverse Flight Characteristics Efficiently by only Two Kalman Filters using Constant Acceleration Model and Adaptive Singer Model.