• 대한전자공학회논문지TC
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• 제42권1호`
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• pp.9-15
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• 2005

현재 위치결정기술에 주로 사용되고 있는 매체는 RF이다. 그러나 RF를 사용한 위치결정기술은 GPS나 실외의 LOS 상황에서 주로 이용되고 있다. 왜냐하면 실내에서는 다중경로 해상도가 좋지 않아 정확한 위치 값을 계산해 내기가 힘들기 때문이다. UWB는 다중경로 해상도가 높고 장애물 투과율이 좋은 실내 측위에 적합한 매체이며 현재 UWB 통신 및 위치측정에 사용하고자 하는 표준화가 IEEE 802.15 위원회에서 진행 중이다. 그러나 UWB를 이용한 실내 측위 알고리즘의 연구나 개발은 아직 미비하다. 본 논문에서는 실내 측위에서 UWB의 장점을 극대화 할 수 있는 TDOA 알고리즘 중 대표적인 두 가지 알고리즘을 분석하고 이를 UWB 실내 측위에 이용할 때 얼마나 정확한 위치를 추정할 수 있는지를 시뮬레이션을 통해 분석한다. 또한 UWB 채널모델을 분석하고 오차요소를 시뮬레이션에 적용하여 그 결과를 비교분석하며, 시뮬레이션 결과를 바탕으로 실내 측위를 위한 UWB의 가능성 및 적합한 알고리즘을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Journal of Positioning, Navigation, and Timing
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• 제9권3호
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• pp.151-156
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• 2020

A technology for calculating the position of a device is very important for users who receive positioning services, regardless of various indoor/outdoor or with/without any positioning infrastructure existence environments. One of the positioning resources widely used at present, LTE, is a typical infrastructure that can overcome the space limitation, however its positioning method based on the position of the LTE base station has low accuracy. A method of constructing a radio wave map of an LTE signal has been proposed as a method for overcoming the accuracy, but it takes a lot of time and cost to perform high-density collection in a wide area. In this paper, we describe a method of creating a high-density DB for the entire region by using vehicle-based partial collection data. To create a positioning database, we applied the idea of Generative Adversarial Network (GAN), which has recently been in the spotlight in the field of deep learning, and learned the collected data. Then, a virtually generated map which having the smallest error from the actual data is selected as the optimum DB. We verified the effectiveness of the positioning DB generation algorithm using the positioning data obtained from un-collected area.

• 한국통신학회논문지
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• 제40권10호
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• pp.2062-2064
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• 2015

본 논문에서는 LED 패널의 신호를 받아 모바일 단말기에 장착된 이미지 센서를 통하여 임의의 위치에 있는 모바일 단말기의 위치를 추정하는 실내 측위 알고리즘을 제안하였다. 측위 성능평가를 위하여 실내에 존재하는 잡음 환경을 고려하였고, 제안한 알고리즘은 잡음환경에 무관하게 높은 측위 성능을 보임을 입증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1618-1622
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• 2004

In this paper, the linearly interpolated PRC(Pseudo Range Correction) regenerating algorithm was applied to improve the DGPS(Differential Global Positioning System) positioning accuracy at user's spot by using the various PRC information obtained from multi-DGPS reference stations. The PRC information of each GPS satellite is not varying rapidly; it is possible to assume that the variation of PRC information of each GPS satellite is linear. So the linearly interpolated PRC regenerating algorithm can be applied to improve the DGPS positioning accuracy at user's spot by using the various PRC information obtained from multi-DGPS reference stations. To test the performance of the linearly interpolated PRC regenerating algorithm, maritime DGPS reference stations' PRC data was used in RTCM format. 11 maritime DGPS reference stations are in service providing DGPS information to public since 1999. Two set of 3 DGPS reference stations are selected to compare the performance of the linearly interpolated PRC regenerating algorithm. The DGPS positioning accuracy was dramatically improved about 40%. Linearly interpolated PRC regenerating algorithm adopted multi-channel DGPS receiver will be developed in near future.

• Journal of Positioning, Navigation, and Timing
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• 제10권2호
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• pp.121-130
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• 2021

In this paper, we propose a method to improve the positioning accuracy of TOA based indoor positioning system in NLOS environments. TOA based indoor positioning systems have been studied mostly considering LOS environments. However, it is almost impossible to maintain the LOS environments due to obstacles such as people, furniture, walls, and so on. The proposed method in this study compensates the range error caused by the NLOS environments. We confirmed that positioning accuracy of a proposed method is improved than conventional algorithms through simulation and field test.

• 한국측량학회지
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• 제34권4호
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• pp.373-382
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• 2016

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.742-747
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• 2004

Outdoors we can easily acquire our accurate location by GPS. However, the GPS signal can't be acquired indoors because of its weak signal power level. Adequate positioning method is demanded for many indoor positioning applications. At present, wireless local area network (WLAN) is widely installed in various areas such as airport, campus, and park. This paper proposes a positioning algorithm using WLAN signal strength to provide the position of the WLAN user indoors. There are two methods for WLAN based positioning, the signal propagation method uses signal strength model over space and the empirical method uses RF power propagation database. The proposed method uses the probability distribution of the power propagation and the maximum likelihood estimation (MLE) algorithm based on power strength DB. Test results show that the proposed method can provide reasonably accurate position information.