• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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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 Advanced Marine Engineering and Technology
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• 제36권1호
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• pp.179-184
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• 2012

기존의 무선 RF 통신은 근거리에서 전력손실이 상대적으로 크고, 전파간섭 및 방해, 재밍 등에 민감하다. 이러한 단점을 보완하는 대안으로 자외선을 이용한 통신 방식에 대한 연구가 최근 관심을 받고 있다. 본 논문에서 자외선을 이용한 비가시거리 통신의 data rate 특성에 대해 시뮬레이션한 결과를 제시하였다. On-off keying 방식을 사용하는 비가시거리 자외선 통신에서 data rate는 송신 빔의 방향, 수신빔의 빔 폭, 송신 전력에 의해 큰 영향을 받는다는 것을 확인하였다.

• Journal of Communications and Networks
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• 제14권5호
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• pp.533-539
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• 2012

The performance analysis of wireless geolocation in a non-line-of-sight (NLOS) environment is a very important issue. Since Cramer-Rao lower bound (CRLB) determines the physical impossibility of the variance of an unbiased estimator being less than the bound, many studies presented the performance analysis in terms of CRLB. Several CRLBs for time-of-arrival (TOA), pseudo-range TOA, angle-of-arrival (AOA), and signal strength (SS) based positioning methods have been derived for NLOS environment. However, the performance analysis of time difference of arrival (TDOA) and TDOA/SS based geolocation techniques in a NLOS environment is still an opening issue. This paper derives the CRLBs of TDOA and TDOA/SS based positioning methods for NLOS environment. In addition, theoretical analysis proves that the derived CRLB for TDOA is the same as that of pseudo-range TOA and the TDOA/SS scheme has a lower CRLB than the TDOA (or SS) scheme.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.760-766
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• 2008

This paper proposes an efficient location technique to find an indoor location under the IEEE 802.11 wireless local area networks. The proposed method is based on the range measurements obtained from a simple radio frequency propagation model. Thus, unlike the radio frequency fingerprint correlation method, it does not suffer from the computational burden during the real-time location service period and can quickly reply the location requests of many users at the same time. To increase the location accuracy in spite of the frequent non-line-of-sight error occurrences, the proposed method calibrates the distortion of the non-line-of-sight error by a simple measurement surveying procedure that does not require the surveyor's manual interaction. Experimental results show the capability of the proposed method.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.361-368
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• 2022

An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

• 한국정보통신학회논문지
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• 제8권2호
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• pp.232-238
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• 2004

본 논문에서는 각각 2.4㎓ 대역과 5.8㎓ 대역에서 팬빔 안테나, 원형편파 안테나 그리고 지향성 안테나를 사용하여 지하철 터널에서의 전파 특성을 실험하였다. 협대역 채널 측정의 격과, NLOS (Non-Line-Of-Sight) 경로에서 수신전력 레벨이 LOS(Line-Of-Sight)에 비하여 급격히 감소함을 보였다. 광대역채널 측정은 PN sliding correlation 방법을 사용하여 수행하였다. 2.4㎓ 대역과 5.8㎓ 대역을 포함하는 IEEE 802.11 무선랜 대역에서 다양한 지향성 빔에 대한 평균초과지연(mean access delay)과 RMS 지연확산(RMS delay spread) 등의 채널 파라미터를 비교하였다.

• 대한임베디드공학회논문지
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• 제5권3호
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• pp.152-156
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• 2010

Non-line-of-sight (NLOS) propagation is one of the challenges in radio positioning. Distinguishing the transmission status of the communication as line-of-sight (LOS) or NLOS is of great importance for the wireless communication systems. This paper focuses on the identification of NLOS based on time-of-arrival (TOA) distance estimates and the received signal strength (RSS) measurements. We set a path loss threshold based on the joint TOA and RSS based NLOS detection method to determine LOS or NLOS. Simulation results show that the proposed method ensures the correct of detection for the LOS condition and can improve the NLOS identification for the weak noise and long distance.

• 한국음향학회지
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• 제18권7호
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• pp.92-100
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• 1999

마이크로셀 이동 통신에서 기지국으로부터 이동국까지의 전파환경을 보다 신속하고 정확히 해석하기 위해 전파의 반사횟수와 전파경로를 연산처리 할 수 있는 삼각해석법 알고리즘을 제안한다. 그리고, 이동국이 가시거리 영역의 전파 음영지역 또는 가시거리 영역과 임의의 경사각으로 기울어져 있는 비가시거리 영역의 전파 음영지역에 위치한 경우를 각각 가정하고 제안 알고리즘을 시뮬레이션하여, 그 결과를 분석함으로써 마이크로셀 이동 통신의 최적 기지국 위치 선정 조건을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4698-4716
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• 2017

Wireless signal transmission is influenced by environmental effects. These effects have also been challenging for Vehicular Ad hoc Network (VANET) in real-time communication. More specifically, in an urban environment, with high mobility among vehicles, a vehicle's status from the transmitter can instantly trigger from line of sight to non-line of sight, which may cause loss of real-time communication. In order to overcome this, a deterministic signal propagation model is required, which has less complexity and more feasibility of implementation. Hence, we propose a realistic path loss model which adopts ray tracing technique for VANET in a grid urban environment with less computational complexity. To evaluate the model, it is applied to a vehicular simulation scenario. The results obtained are compared with different path loss models in the same scenario based on path loss value and application layer performance analysis. The proposed path loss model provides higher loss value in dB compared to other models. Nevertheless, the performance of vehicle-vehicle communication, which is evaluated by the packet delivery ratio with different vehicle transmitter density verifies improvement in real-time vehicle-vehicle communication. In conclusion, we present a realistic path loss model that improves vehicle-vehicle wireless real-time communication in the grid urban environment.

• 한국산학기술학회논문지
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• 제11권4호
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• pp.1248-1253
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• 2010

본 논문은 SDS-TWR(Symmetric Double-Sided Two-Way Ranging)의 Ranging 오차를 보정하기 위하여 균등거리비율 개념을 적용한 위치인식 보정 알고리즘인 AEDR(Algorithm for localization using the concept of Equivalent Distance Rate)을 제안하고, 위치인식 실험을 통해 위치인식 측정 성능을 분석하였다. SDS-TWR의 Ranging 오차는 실험에 의하면 비콘노드와 이동노드의 특정 거리구간에서 평균 1m~8m로 측정되었다. 그러나 제안한 AEDR에 의한 위치인식 성능은 실험을 통해 전체적으로 교내 강당과 복도 모두에서 SDS-TWR 보다 4배 정도 우수하였으며, 측정된 3~10m 이상의 위치인식 오차를 평균 2m 내외로, 3m 이내의 위치인식 오차를 평균 1m 내외로 각각 감소시킬 수 있음을 확인하였다. 특히 AEDR은 LOS(Line Of Sight) 보다 NLOS(Non Line Of Sight)에서 훨씬 더 위치인식 보정 성능이 우수함을 나타내며, 대부분의 센서 네트워크의 환경이 NLOS임을 고려할 때 AEDR이 실제환경에서의 위치인식에 큰 도움을 줄 수 있다고 판단된다.