• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.20-25
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• 2006

Low frequency towed line array with high array gain and beam resolution is a long range surveillance sensor for anti-submarine warfare. The beam characteristics is however deteriorated due to the distorted line array sensor caused by low towing speed, wind, current, and towing ship maneuvering. An adaptive beamforming method is utilized in this paper to enhance the distorted line array beam performance by estimating and compensating the nonlinear array shape. A polynomial curve fitting in the least square sense is used to estimate the array shape iteratively with the distributed heading sensors data along the array. Real time array shape estimation and nonlinear array beam calculation is applied to a very long towed line array sensor system and the beam performance is evaluated and compared to the linear beamformer for the simulation and sea trial data.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.142-148
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• 2004

In this paper, to detect exciting frequency on the latticed fence structure, fiber optic sensor using Sagnac interferometer was fabricated and tested. The latticed structure fabricated with dimension of 180 cm wide and 180 cm high, the optical fiber, 50 m in length, distributed and fixed on the latticed structure. Single mode fiber, a laser with 1,550 m wavelength, and $3{\times}3$ coupler were used. Excited vibration signal applied to the latticed structure from 200 Hz to 1 KHz. The detected optical signals were compared to the detected acceleration signals and analyzed on the time and frequency domain. Based on the experimental results, fiber optic sensor using Sagnac interferometer detected exciting frequency, effectively. This system can be applied to the structural health monitoring system.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.607-608
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• 2012

Data aggregation is a fundamental problem in wireless sensor networks which attracts great attention in recent years. Delay and energy efficiencies are two crucial issues of designing a data aggregation scheme. In this paper, we propose a distributed, energy efficient algorithm for collecting data from all sensor nodes with the minimum latency called Delay-aware Power-efficient Data Aggregation algorithm (DPDA). The DPDA algorithm minimizes the latency in data collection process by building a time efficient data aggregation network structure. It also saves sensor energy by decreasing node transmission distances. Energy is also well-balanced between sensors to achieve acceptable network lifetime. From intensive experiments, the DPDA scheme could significantly decrease the data collection latency and obtain reasonable network lifetime compared with other approaches.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.114-122
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• 2021

In this paper, an automated vehicle intersection collision accident was analyzed through simulation. Recently, the more automated vehicles are distributed, the more accidents related to automated vehicles occur. Accidents may show different trends depending on the sensor characteristics of the automated vehicle and the performance of the accident prevention system. Based on NASS-CDS (National Automotive Sampling System-Crashworthiness Data System) and TAAS (Traffic Accident Analysis System), four scenarios are derived and simulations are performed. Automated vehicles are applied with a virtual system consisting of an autonomous emergency braking system and algorithms that predict the route and avoid collisions. The simulations are conducted by changing the sensor angle, vehicle speed, the range of the sensor and vehicle speed range. A range of variables considered vehicle collision were derived from the simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.85-97
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• 2011

Wireless sensor networks have emerged as one of the key enabling technologies for ubiquitous computing since wireless intelligent sensor nodes connected by short range communication media serve as a smart intermediary between physical objects and people in ubiquitous computing environment. We recognize the wireless sensor network as a massively distributed and deeply embedded system. Such systems require concurrent and asynchronous event handling as a distributed system and resource-consciousness as an embedded system. Since the operating environment and architecture of wireless sensor networks, with the seemingly conflicting requirements, poses unique design challenges and constraints to developers, we propose a very new operating system for sensor nodes based on finite state machine. In this paper, we clarify the design goals reflected from the characteristics of sensor networks, and then present the heart of the design and implementation of a compact and efficient state-driven operating system, SenOS. We describe how SenOS can operate in an extremely resource constrained sensor node while providing the required reactivity and dynamic reconfigurability with low update cost. We also compare our experimental results after executing some benchmark programs on SenOS with those on TinyOS.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.166-171
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• 2023

Efficient energy management is a very important factor in sensor networks with limited resources, and cluster techniques have been studied a lot in this respect. However, a problem may occur in which energy use of the cluster header is concentrated, and when the cluster header is not evenly distributed over the entire area but concentrated in a specific area, the transmission distance of the cluster members may be large or very uneven. The transmission distance can be directly related to the problem of energy consumption. Since the energy of a specific node is quickly exhausted, the lifetime of the sensor network is shortened, and the efficiency of the entire sensor network is reduced. Thus, balanced energy consumption of sensor nodes is a very important research task. In this study, factors for balanced energy consumption by cluster headers and sensor nodes are analyzed, and a balancing distribution clustering method in which cluster headers are balanced distributed throughout the sensor network is proposed. The proposed cluster method uses multi-hop routing to reduce energy consumption of sensor nodes due to long-distance transmission. Existing multi-hop cluster studies sets up a multi-hop cluster path through a two-step process of cluster setup and routing path setup, whereas the proposed method establishes a hierarchical cluster routing path in the process of selecting cluster headers to minimize the overhead of control messages.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.443-450
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• 2016

In this study, we propose a novel fiber optic sensor to show the measurement feasibility of distributed temperature and strains in a single sensing fiber line. Distributed temperature can be measured using optical time domain reflectometry (OTDR) with a Raman anti-Stokes light in the sensing fiber line. Moreover, the strain can be measured by fiber Bragg gratings (FBGs) in the same sensing fiber line. The anti-Stokes Raman back-scattering lights from both ends of the sensing fiber, which consists of a 4 km single mode optical fiber, are acquired and inserted into a newly formulated equation to calculate the temperature. Furthermore, the center wavelengths from the FBGs in the sensing fiber are detected by an optical spectrum analyzer; these are converted to strain values. The initial wavelengths of the FBGs are selected to avoid a cross-talk with the wavelength of the Raman pulsed pump light. Wavelength shifts from a tension test were found to be 0.1 nm, 0.17 nm, 0.29 nm, and 0.00 nm, with corresponding strain values of $85.76{\mu}{\epsilon}$, $145.55{\mu}{\epsilon}$, $247.86{\mu}{\epsilon}$, and $0.00{\mu}{\epsilon}$, respectively. In addition, a 50 m portion of the sensing fiber from $30^{\circ}C$ to $70^{\circ}C$ at $10^{\circ}C$ intervals was used to measure the distributed temperature. In all tests, the temperature measurement accuracy of the proposed sensor was less than $0.50^{\circ}C$.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.9-17
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• 2014

This paper proposes a binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization using the value of the measured distances from three or more neighboring anchors, i.e., nodes that know their location information. The node that is localized during the localization process is then used as another anchor for remaining nodes. The performances of particle swarm optimization (PSO) and BPSO in terms of localization error and computation time are compared by using simulations in Matlab. The simulation results indicate that PSO-based localization is more accurate. In contrast, BPSO algorithm performs faster for finding the location of unknown nodes for distributed localization. In addition, the effects of transmission range and number of anchor nodes on the localization error and computation time are investigated.

• Journal of Sensor Science and Technology
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• v.31 no.3
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• pp.163-167
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• 2022

In this study, we investigated a carbon nanotube (CNT) film sensor to detect hazardous and noxious substances distributed in seawater. The response change of the sensor was studied according to environmental temperature, and its temperature coefficient of resistance (TCR, α) was measured. The temperature of the CNT film (~50 ㎛) was in the range of 20-50 ℃, and αCNT was calculated to be -0.0011 %/ ℃. We experimentally confirmed that the CNT film had a smaller TCR value than that of the conventional sensor. Therefore, we investigated the response change of the CNT sensor according to temperature. The CNT sensor showed a relatively small error of approximately 2.3 % up to 30 ℃, which is within the temperature range of the seawater of the Korean Peninsula. However, when the temperature exceeded 40 ℃, the error in the CNT sensor increased by more than 5.2 %. We fabricated a metal oxide (ITO, indium-tin-oxide) film and compared its performance with that of the CNT sensor. The ITO sensor showed an error of >12.5 % at 30 ℃, indicating that in terms of the stability of the sensor to temperature, the CNT film sensor has superior performance.