• 한국해양공학회지
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• 제19권2호
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• pp.82-89
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• 2005

This study deals with the development of the extended Kalman filter(EKF) algorithm for the localization of underwater mining vehicles. Both simulation and experimental studies in a test bed are carried out. For the experiments, a scale dawn tracked vehicle is run in a soil bin containing cohesive soil of bentonite-water mixture. To develop the EKF algorithm, we use a kinematic model including the inner/outer track slips and the slip angle for the vehicle. The measurements include the inner and outer wheel speeds from encoders, the heading angle from a compass sensor and a fiber optic rate gyro, and x and y coordinate position values from a vision system. The vision sensor replaces the LBL(Long Base Line) sonar system used in the real underwater positioning situations. Artificial noise signals mimicking the real LBL noise signal are added to the vision sensor information. To know the mean slip values of the tracks in both straight and cornering maneuver, several trial running experiments are executed before applying the EKF algorithm. Experimental results show the effectiveness of the EKF algorithm in rejecting the sensor measurements noise. Also, the simulation and experimental results show close correlations.

• ETRI Journal
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• 제37권4호
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• pp.824-832
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• 2015

Heart sounds are the main obstacle in lung sound analysis. To tackle this obstacle, we propose a diagnosis algorithm that uses singular spectrum analysis (SSA) and frequency features of heart and lung sounds. In particular, we introduce a frequency coefficient that shows the frequency difference between heart and lung sounds. The proposed algorithm is applied to a synthetic mixture of heart and lung sounds. The results show that heart sounds can be extracted successfully and localizations for the first and second heart sounds are remarkably performed. An error analysis of the localization results shows that the proposed algorithm has fewer errors compared to the SSA method, which is one of the most powerful methods in the localization of heart sounds. The presented algorithm is also applied in the cases of recorded respiratory sounds from the chest walls of five healthy subjects. The efficiency of the algorithm in extracting heart sounds from the recorded breathing sounds is verified with power spectral density evaluations and listening. Most studies have used only normal respiratory sounds, whereas we additionally use abnormal breathing sounds to validate the strength of our achievements.

• 한국컴퓨터정보학회논문지
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• 제12권4호
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• pp.269-277
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• 2007

진보된 하드웨어 개발 기술 및 다양한 응용 가능성으로 인하여 무선 센서 네트워크 시스템이 현재 또는 미래에 주목받을 것으로 기대된다. 최근 다양한 응용 중에서 해안 및 수중 센서 네트워크 시스템에 대한 관심이 증대되고 있다. 센서 네크워크 시스템을 해양 및 수중에 적용하여 해양 자원 샘플링, 환경 모니터링, 재해 예방, 항로 유도 등 다양한 이점을 얻을 수 있다. 그러나 이러한 응용을 위해서 센서 노드의 위치 정보가 제공되어야 한다. 따라서 해양 및 수중 환경에서 센서 노드들의 위치 정보를 얻기 위해 순차적인 위치 파악(Sequential Localization) 알고리즘을 제안한다. 순차적 위치 파악은 해안가에 적은 수의 비콘 노드를 설치하여 센서 노드의 위치를 파악한다. 순차적인 위치 파악(Sequential Localization) 방법은 위치 에러 누적 현상을 완화하고 최대한 센서 노드들의 위치 파악을 위해 센서 노드들의 위치 파악 순서를 제어하여 위치 정보를 얻는다. 순차적 위치 파악은 센서 노드들의 레퍼런스 노드의 개수에 대한 정보를 가지고 각 센서 노드의 위치 파악 순서를 지정한다. 가장 많은 레퍼런스 노드를 가지는 센서 노드가 위치 파악 시 가장 높은 우선순위를 갖는다. 순차적 위치 파악 알고리즘은 위치 에러 성능뿐만 아니라 최대한의 센서 노드의 위치 좌표를 구하여 센서 네트워크의 커버리지 또한 증대시킨다.

• 한국통신학회논문지
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• 제34권8A호
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• pp.575-582
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• 2009

본 논문에서는 RSS(Received Signal Strength) 기반 무선 센서네트워크에서의 거리 식별코드를 이용한 거리측정 알고리즘(LAtu)을 제안하고 이를 기반으로 위치인식시스템을 설계 및 구현하였다. 또한 제안한 거리측정 알고리즘의 Ranging 정확도 성능과, 제안한 거리측정 알고리즘을 적용해서 개발한 위치인식시스템(System(LAtu))의 위치측정 오차 성능을 실제 위치인식 실험을 통해 IEEE 802.15.4 표준규격의 채널모델(LAieee)을 적용한 위치인식 시스템(System(LAieee))과 비교분석하였다. 성능분석의 결과, Ranging 정확도의 성능은 이동모듈과 비콘모듈간의 거리($D_{MM-BM}$)가 2m의 경우는 LAtu가 IEEE 802.15.4 표준규격의 채널모델(LAieee) 보다 34%정도 더 우수하였고, $D_{MM-BM}$가 5m 이상인 경우에서도 LAtu가 LAieee 보다 평균 5% 정도 더 정확하였다. System(LAtu)의 위치측정 오차 성능은 System(LAieee)에 비해 강당에서 1cm, 강의실에서 4cm 정도로 근소하게 낮았다.

• 정보과학회 논문지
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• 제43권1호
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• pp.13-26
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• 2016

본 연구에서는 임의 공간에서 정사면체 형태의 마이크로폰 어레이(microphone array)를 이용하여 음원(sound source)추적 성능을 개선할 수 있는 알고리즘을 제안하였다. 음원추적 시스템은 마이크로폰 어레이의 각 마이크로폰에 도착하는 음원신호의 도착 지연시간(TDOA, Time Delay Of Arrival) 정보를 이용하여 음원의 방향성 정보를 추정한다. 임의 3차원 공간에서 음원추적을 위해서는 최소 3개 이상의 마이크로폰이 필요하다. 3개 마이크로폰으로 구성된 음원추적 시스템의 경우 만약 1개의 마이크로폰이라도 신호 오차가 발생한다면 정확한 음원 방향성 추정이 불가능하다. 본 연구에서는 이러한 문제점을 개선하기 위하여 1개의 마이크로폰을 추가한 정사면체 형태(tetrahedron shaper)의 마이크로폰 어레이를 구성하고 좌표변환 기법을 이용하여 주변 잡음이나 오류에 강인한 새로운 음원추적 알고리즘을 제안하였다. 제안 알고리즘의 성능을 입증하기 위하여 3개의 마이크로폰을 이용한 삼각형 기반 음원추적 시스템과 본 연구에서 제안한 정사면체 기반 음원추적 시스템에 대하여 실시간 비교 실험을 수행하였으며, 실험 결과 제안된 정사면체 기반의 시스템이 최대 약 16% 이상의 향상된 검출율을 보였다.

• 로봇학회논문지
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• 제10권1호
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• pp.1-8
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• 2015

This paper proposes a study for accurate surface localization system using DWT(Discrete Wavelet Transform) and GPS/INS fusion algorithm. Because the propagation in the underwater is not passed by characteristics of the medium unlike the ground, the sonar system like DVL is used instead of GPS. But since these systems are installed on the seafloor and operated, a long time is required for installation and navigation systems are limited outside of the range area. And it is difficult to estimate position in a three-dimensional considering the depth in actual marine environment. In this paper, before the development of underwater localization system, precisely estimated position system is proposed in a two-dimensional by developing surface localization system using removing noise and disturbance with DWT and relatively inexpensive GPS and INS sensor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.703-722
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• 2016

Passive wireless devices have increasing civilian and military applications, especially in the scenario with wearable devices and Internet of Things. In this paper, we study indoor localization of a target equipped with radio-frequency identification (RFID) device in ultra-wideband (UWB) wireless networks. With known room layout, deterministic multipath components, including the line-of-sight (LOS) signal and the reflected signals via multipath propagation, are employed to locate the target with one transmitter and a single inaccurate receiver. A factor graph corresponding to the joint posterior position distribution of target and receiver is constructed. However, due to the mixed distribution in the factor node of likelihood function, the expressions of messages are intractable by directly applying belief propagation on factor graph. To this end, we approximate the messages by Gaussian distribution via minimizing the Kullback-Leibler divergence (KLD) between them. Accordingly, a parametric message passing algorithm for indoor passive localization is derived, in which only the means and variances of Gaussian distributions have to be updated. Performance of the proposed algorithm and the impact of critical parameters are evaluated by Monte Carlo simulations, which demonstrate the superior performance in localization accuracy and the robustness to the statistics of multipath channels.

• Journal of Communications and Networks
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• 제18권5호
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• pp.796-805
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• 2016

In many wireless sensor network (WSN) applications, the information transmitted by an individual entity or node is of limited use without the knowledge of its location. Research in node localization is mostly geared towards multi-hop range-free localization algorithms to achieve accuracy by minimizing localization errors between the node's actual and estimated position. The existing localization algorithms are focused on improving localization accuracy without considering efficiency in terms of energy costs and algorithm convergence time. In this work, we show that our proposed localization scheme, called DV-maxHop, can achieve good accuracy and efficiency. We formulate the multi-objective optimization functions to minimize localization errors as well as the number of transmission during localization phase. We evaluate the performance of our scheme using extensive simulation on several anisotropic and isotropic topologies. Our scheme can achieve dual objective of accuracy and efficiency for various scenarios. Furthermore, the recently proposed algorithms require random uniform distribution of anchors. We also utilized our proposed scheme to compare and study some practical anchor distribution schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권12호
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• 한국군사과학기술학회지
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• 제15권6호
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• pp.729-737
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• 2012

In case that multiple jammers are transmitting the signals which are the same type a general algorithm based on TDOA method cannot estimate the positions of multiple jammers because there are many TDOA measurements including true and false values. This paper, therefore, designs a new algorithm based on TDOA method to localize multiple jammers. In this algorithm, TDOA measurements are obtained by rotating the reference sensor, and then the positions of multiple jammers can be estimated by detecting congregated point among the multiple estimated positions from TDOA measurements. Through computer simulations, it is verified that this algorithm localizes the multiple jammers well. The performance of the algorithm are also analysed by changing the distance between sensors and jammer, and sampling frequency.