• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.541-552
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• 2016

Purpose: In this study, we propose that how to approach a effective system engineering and optimize system engineering management process for the mass production weapon system parts localization development process and success in DTaQ. Methods: To approach a effective system engineering for the mass production weapon system parts localization, we analyze a weapon system acquisition process and system engineering process of Republic of Korea and DTaQ parts localization business regulations in advance. after results of analysis of them, we implement a optimized parts localization development system engineering based on ISO/IEC/IEEE 15288. Results: In order to apply International Standard ISO/IEC/IEEE 15288 to the mass production weapon system parts localization development process, we compare the mass production weapon system parts localization acquisition environment with ISO/IEC/IEEE 15288 and analyze them. therefore, It is possible to implement a part of concept stage and development stage of ISO/IEC/IEEE total life cycle stage for the mass production weapon system parts localization development process. To achieve the technical review milestones of DTaQ parts localization business regulations in the selected stages of ISO/IEC/IEEE, the development and management agency perform 2 high rank process and 19 low rank process specified in ISO/IEC/IEEE. Conclusion: When the development and management agency perform the mass production weapon system parts localization development using the proposed system engineering approach, they should easily meet milestone through the clarified requirement and simplified System Engineering output documents in limited development period.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.312-319
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• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• Korean Management Science Review
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• v.29 no.3
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• pp.1-11
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• 2012

This paper considers a localization problem in time difference of arrival (TDOA)-based radio frequency identification (RFID) systems. To estimate the position of a target tag, this paper suggests three localization algorithms that use benchmark tags. The benchmark tags are the same type as the target tag, but either the locations or distance of the benchmark tags are known. Two algorithms use the benchmarks for auxiliary information to improve the estimation accuracy of the other localization algorithms such as least squared estimator (LSE). The other one utilizes the benchmarks as essential tags to estimate the location. Numerical tests show that the localization accuracy can be improved by using benchmark tags especially when an algorithm using the LSE is applied to the localization problem. Furthermore, this paper shows that our benchmark algorithm is valuable when the measurement noise is large.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.845-850
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• 2009

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.55-62
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• 2016

In this paper, we present indoor localization technologies using the bluetooth signal categorizing them into proximity based, triangulation based and fingerprinting based technologies. Then we provide localization accuracy improvement algorithms such as moving average, K-means, particle filter, and K-Nearest neighbor algorithms. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Finally we provide experimental results for correlation between RSSI and distance. We believe that this paper provide wise view and necessary information for recent localization technologies using the bluetooth signal.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.89-94
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• 2011

Underwater localization is a crucial capability for reliable operation of various types of underwater vehicles including submarines and underwater robots. However, sea water is almost impermeable to high-frequency electromagnetic waves, and thus absolute position fixes from Global Positioning System (GPS) are not available in the water. The use of acoustic telemetry systems such as Long Baseline (LBL) is a practical option for underwater localization. However, this telemetry network system needs to be pre-deployed and its availability cannot always be assumed. This study focuses on demonstrating the validity of terrain-based localization techniques in a GPS-denied underwater environment. Since terrain-based localization leads to a nonlinear estimation problem, nonlinear filtering methods are required to be employed. The extended Kalman filter (EKF) which is a widely used nonlinear filtering algorithm often shows limited performance under large initial uncertainty. The feasibility of using a particle filter is investigated, which can improve the performance and reliability of the terrain-based localization.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.429-437
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• 2005

Sensor localization has become an essential requirement for realistic applications over wireless sensor networks (WSN). In this paper we propose an ad hoc localization algorithm that is infrastructure-free, anchor-free, and computationally efficient with reduced communication. A novel combination of distance and direction estimation technique is introduced to detect and estimate ranges between neighbors. Using this information we construct unidirectional coordinate systems to avoid the reflection ambiguity. We then compute node positions using a transformation matrix [T], which reduces the computational complexity of the localization algorithm while computing positions relative to the fixed coordinate system. Simulation results have shown that at a node degree of 9 we get $90\%$ localization with $20\%$ average localization error without using any error refining schemes.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.23-31
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• 2020

It is essential to estimate the vehicle localization for an autonomous safety driving. In particular, since LIDAR provides precise scan data, many studies carried out to estimate the vehicle localization using LIDAR and pre-generated map. The road marking always exists on the road because of provides driving information. Therefore, it is often used for map information. In this paper, we propose to generate the Gaussian mixture map based on road-marking information and localization method using this map. Generally, the probability distributions map stores the single Gaussian distribution for each grid. However, single resolution probability distributions map cannot express complex shapes when grid resolution is large. In addition, when grid resolution is small, map size is bigger and process time is longer. Therefore, it is difficult to apply the road marking. On the other hand, Gaussian mixture distribution can effectively express the road marking by several probability distributions. In this paper, we generate Gaussian mixture map and perform vehicle localization using Gaussian mixture map. Localization performance is analyzed through the experimental result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.87-107
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• 2015

Considering the localization estimation issue in mixed line-of-sight (LOS)/non-LOS(NLOS) environments based on received signal strength (RSS) measurements in wireless sensor networks, a grid-based correlation method based on the relationship between distance and RSS is proposed in this paper. The Maximum-Likelihood (ML) estimator is appended to further improve the localization accuracy. Furthermore, in order to reduce computation load and enhance performance, an improved recursively version with NLOS mitigation is also proposed. The most advantages of the proposed localization algorithm is that, it does not need any prior knowledge of the propagation model parameters and therefore does not need any offline calibration effort to calibrate the model parameters in harsh environments, which makes it more convenient for rapid implementation in practical applications. The simulation and experimental results evidence that the proposed localization algorithm exhibits good localization performance and flexibilities for different devices.

• Journal of Sensor Science and Technology
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• v.17 no.1
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• pp.53-60
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• 2008

Localization is the most important functions in mobile robots. There are so many approaches to realize this essential function in wheel based mobile robots, but it is not easy to find similar examples in small underwater robots. It is presented the sonar localization system using ubiquitous sensor network for a fish robot in this paper. A fish robot uses GPS and sonar system to find exact localization. Although GPS is essential tool to obtain positional information, this device doesn't provide reasonable resolution in localization. To obtain more precise localization information, we use several Ubiquitous Sensor Networks (USN) motes with sonar system. Experimental results show that a fish robot obtains more detailed positional information.