• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.65-75
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• 2009

In Wireless Sensor Network, the sensor node localization is important issue for information tracking, event detection, routing. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning system, then all the other nodes are approximately localized using various algorithms based on a coordinate system of anchor DV-Hop is a localized, distributed, hop by hop positioning algorithm in wireless sensor network where only a limited fraction of nodes have self positioning capability. However, instead of uniformly distributed network, in anisotropic network with possible holes, DV-Hop's performance is very low. To address this issue, we propose Group based DV-Hop (GDV-Hop) algorithm. Best contribution of GDV-Hop is that it performs localization with reduced error compared with DV-Hop in anisotropic network.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.184-190
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• 2006

Recently, Lee et al. have proposed an algorithm utilizing the signals from different paths by using bottom mounted simple linear array to estimate 3-D location of oceanic target. But this algorithm assumes that sound velocity is constant along depth of sea. Consequently, serious performance loss is appeared in real oceanic environment that sound speed is changed variously. In this paper, we present a 3-D near field localization algorithm for inhomogeneous sound speed. The proposed algorithm adopt localization function that utilize ray propagation model for multipath environment with linear sound speed profile(SSP), after that, the proposed algorithm searches for the instantaneous azimuth angle, range and depth from the localization cost function. Several simulations using linear SSP and non linear SSP similar to that of real oceans are used to demonstrate the performance of the proposed algorithm. The estimation error in range and depth is decreased by 100m and 50m respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1317-1340
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• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.251-257
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• 2021

An underwater platform operating a passive sonar needs to acquire the target position to perform its mission. In an environment where sea-floor reflections exist, the position of a target can be estimated using the difference in the arrival time between the signals received through multipaths. In this paper, a method of localization for passive sonar is introduced, based on the EKF (Extended Kalman Filter) using the multipath time difference of arrival in underwater environments. TMA (Target Motion Analysis) requires accumulated measurements for long periods and has limitations on own-ship movement, allowing it to be used only in certain situations. The proposed method uses an EKF, which takes measurements of the time differences of the signal arrival in multipath environments. The method allows for target localization without restrictions on own-ship movement or the need for an observation time. To analyze the performance of the proposed method, simulation according to the distance and depth of the target was performed repeatedly, and the localization error according to the distance and water depth were analyzed. In addition, the correlation with the estimated position error was assessed by analyzing the arrival time difference according to the water depth.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.318-327
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• 2009

In this paper, we propose a 3-D geometric localization method for near-field broadband source in shallow water environments. According to the waveguide invariant theory, slope of the interference pattern which is seen in a sensor spectrogram directly proportional to a range of the source. The relative ratio of the range between source and sensors was estimated by matching of two interference patterns in spectrogram. Then this ratio is applied to the Apollonius's circle which shows the locus of a source whose range ratio from two sensors is constant. Two Apollonius's circles from three sensors make the intersection point that means the horizontal range and the azimuth angle of the source. And this intersection point is constant with source depth. Therefore the source depth can be estimated using 3-D hyperboloid equation whose range difference from two sensors is constant. To evaluate a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program and analysis of localization error is demonstrated. From simulation results, error estimate for range and depth is described within 50 m and 15 m respectively.

• Ocean Systems Engineering
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• v.9 no.4
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• pp.391-407
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• 2019

Tracking the location (position) of a surface or underwater marine vehicle is important as part of guidance and navigation. While the Global Positioning System (GPS) works well in an open sea environment but its use is limited whenever testing scaled-down models of such vehicles in the laboratory environment. This paper presents the design, development and implementation of a low energy ultrasonic augmented single beacon-based localization technique suitable for such requirements. The strategy consists of applying Extended Kalman Filter (EKF) to achieve location tracking from basic dynamic distance measurements of the moving model from a fixed beacon, while on-board motion sensor measures heading angle and velocity. Iterative application of the Extended Kalman Filter yields x and y co-ordinate positions of the moving model. Tests performed on a free-running ship model in a wave basin facility of dimension 30 m by 30 m by 3 m water depth validate the proposed model. The test results show quick convergence with an error of few centimeters in the estimated position of the ship model. The proposed technique has application in the real field scenario by replacing the ultrasonic sensor with industrial grade long range acoustic modem. As compared with the existing systems such as LBL, SBL, USBL and others localization techniques, the proposed technique can save deployment cost and also cut the cost on number of acoustic modems involved.

• Progress in Medical Physics
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• v.5 no.1
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• pp.41-53
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• 1994

The accurate localization of electrical sources in the brain is one of the most important questions in EEG, especially in the analysis of evoked responses and of epileptiform spike activity. A detailed simulation study of single dipole source estimation based on EEG is given in this paper. The effects of dipole model parameters on single dipole source tracing in EEG are examined in some detail using the Monte Carlo simulation. The error of source localization is found to be greatly influenced by how the electrodes are distributed over the head and the number of them.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.28-32
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• 2007

While various methods for sound source localization have been developed, most of them utilize on the time difference of arrival (TDOA) between microphones or the measured head related transfer functions (HRTF). In case of a real robot implementation, the former has a merit of light computation load to estimate the sound direction but can not consider the effect of platform on TDOAs, while the latter can, because characteristics of robot platform are included in HRTF. However, the latter needs large resources for the HRTF database of a specific robot platform. We propose the compensation method which has the light computation load while the effect of platform on TDOA can be taken into account. The proposed method is used with spherical head related transfer function (SHRTF) on the assumption that robot platform, for example a robot head, installed microphones can be modeled to a sphere. We verify that the proposed method decreases the estimation error caused by the robot platform through the simulation and experiment in real environment.