• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.49-54
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• 2011

In this paper, we represent a mobile robot which can recognize chemical odor, measure concentration, and track its source indoors. The mobile robot has the function of smell that can sort several gases in experiment such as ammonia, ethanol, and their mixture with neural network algorithm and measure each gas concentration with fuzzy rules. In addition, it can not only navigate to the desired position with vision system by avoiding obstacles but also transmit odor information and warning messages earned from its own operations to other nodes by multi-hop communication in wireless sensor network. We suggest the way of odor sorting, concentration measurement, and source tracking for a mobile robot in wireless sensor network using a hybrid algorithm with vision system and gas sensors. The experimental studies prove that the efficiency of the proposed algorithm for odor recognition, concentration measurement, and source tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.164-171
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• 2010

We have studied the port-automation system which is requested by the steep increment of cost and complexity for processing the freight. This paper will introduce a new algorithm for navigating and controlling the autonomous Guided Vehicle (AGV). The camera has the optical distortion in nature and is sensitive to the external ray, the weather, and the shadow, but it is very cheap and flexible to make and construct the automation system for the port. So we tried to apply to the AGV for detecting and tracking the lane using the CCD camera. In order to make the error stable and exact, this paper proposes new concept and algorithm for obtaining the error is generated by the Virtual Photo-Sensor Array (VPSA). VPSAs are implemented by programming and very easy to use for the various autonomous systems. Because the load of the computation is light, the AGV utilizes the maximal performance of the CCD camera and enables the CPU to take multi-tasks. We experimented on the proposed algorithm using the mobile robot and confirmed the stable and exact performance for tracking the lane.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.306-314
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• 2013

Automatic tracking in cluttered environment requires the initiation and maintenance of tracks, and track existence probability of true track is kept by Markov Chain Two model of target existence propagation. Unlike Markov Chain One model for target existence propagation, Markov Chain Two model is made up three hypotheses about target existence event which are that the target exist and is detectable, the target exists and is non-detectable through occlusion, and the target does not exist and is non-detectable according to non-existing target. In this paper we present multi-scan single target tracking algorithm based on the target existence, which call the Integrated Track Splitting algorithm with Markov Chain Two model in imaging sensor.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.24-31
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• 2005

This paper presents an implementation of a real-time multi-sensor data fusion algorithm for Flight Test Computer. The sensor data consist of positional information of the target from a radar, a GPS receiver and an INS. The data fusion algorithm is designed by the 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad measurements and sensor faults. The statistical parameters for the states are obtained from Monte Carlo simulations and covariance analysis using test tracking data. The designed filter is verified by using real data both in post processing and real-time processing.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.920-922
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• 2018

This paper describes a method to classify simple circular artificial markers on surfaces of a box on the back of hand to detect the pose of user's hand for VR/AR applications by using a Leap Motion camera and two IMU sensors. One IMU sensor is located in the box and the other IMU sensor is fixed with the camera. Multi-layer Perceptron (MLP) algorithm is adopted to classify artificial markers on each surface tracked by the camera using IMU sensor data. It is experimented successfully in real-time, 70Hz, under PC environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.119-125
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• 2022

The power supply for the anti-aircraft radar homing sensor should allow the system to receive power quickly and stably without the influence of noise. For this purpose, DC-DC converters are widely used for reliable power conversion. Also, switching of DC-DC converters Frequency noise should not cause false alarms and ghosts that may affect the detection and tracking performance of the system, and it should have a check function that can monitor power in real time while the homing sensor is operating. In order to apply to anti-aircraft radar homing sensor, we developed a multi-output switching power supply with maximum output 𐩒𐩒𐩒 W, efficiency 80% or more (@100% load), output power by receiving 28VDC input, and power supply to achieve more than 80% efficiency. A DC-DC converter was applied to this large output, and the multi-output flyback method was applied to the rest of the low-power output.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.11
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• pp.1171-1177
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• 2009

A missile warning radar is an essential sensor for active protection system to detect antitank missile in all weather environments. This paper introduces missile warning radar for main battle tank and presents the results of the design and implementation of the radar signal processor using high speed multi-DSP. The key algorithms include adaptive CF AR, weighted linear fitting algorithm, S/W tracking capability, and threat decision and present test result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.180-186
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• 2017

In this paper we propose a traffic aware Demand Wakeup MAC(TADW-MAC) protocol, in which low data delay and high throughput can be achieved, for wireless sensor networks. With the TADW-MAC protocol, the problem of the DW-MAC protocol, which schedules only one packet to deliver during the Sleep period in a multi-hop transmission is resolved. DW-MAC is not adequate for the applications such as object tracking and fire detection, in which busty data should be transmitted in a limited time when an event occurs [6-8]. When an event occurs, duty cycle can be adjusted in the TADW-MAC protocol to get less energy consumption and low latency. The duty cycle mechanism has been widely used to save energy consumption of sensor node due to idle listening in wireless sensor networks. But additional delay in packet transmission may be increased in the mechanism. Our simulation results show that TADW-MAC outperforms RMAC and DW-MAC in terms of energy efficiency while achieving low latency.