Cellular Base Station Assisted Indoor Positioning

2019 ◽  
Vol 55 (2) ◽  
pp. 592-606 ◽  
Author(s):  
Xiukui Li

2014 ◽  
pp. 103-109
Author(s):  
Uwe Grossmann ◽  
Markus Schauch ◽  
Syuzanna Hakobyan

Often mobile devices like mobile phones or personal digital assistants (PDA) are equipped with IEEE 802.11 WLAN adapters. Furthermore, within many buildings a WLAN infrastructure is available. The aim of this work is to investigate the quality of different indoor positioning methods based on values of WLAN received signal strength index (RSSI) using commercially available devices (mobile phones, PDA). Three positioning algorithms were considered: minimal Euclidian distance, intersections of RSSI-Isolines and a stochastic model based on Bayes' theorem. Two measuring testbeds, a museum's exhibition room and an empty seminar room, four different types of PDA (Dell, Fujitsu, HP, T-Mobile) and two types of access points (Netgear, Lancom) were used. Results show that positioning can be achieved with an average accuracy of approx. 2-3 metres. WLAN capable mobile devices behave differently in receiving RSSI values of a base station. For reasons of standardization a linear correlation between different receiving levels of PDA was investigated.



2021 ◽  
Author(s):  
Mei Wang ◽  
Fan Yang ◽  
Zou Zhou ◽  
Hongbing Qiu




Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 33
Author(s):  
Xiaofei Yang ◽  
Jun Wang ◽  
Hui Ye ◽  
Jianzhen Li

In the global positioning system (GPS) denied environment, an indoor positioning system based on ultra-wide band (UWB) technology has been utilized for target location and navigation. It can provide a more accurate positioning measurement than those based on received signal strength (RSS). Although promising, it suffers from some shortcomings that base stations should be preinstalled to obtain reference coordinate information, just as navigation satellites in the GPS system. In order to improve the positioning accuracy, a large number of base stations should be preinstalled and assigned coordinates in the large-scale network. However, the coordinate setup process of the base stations is cumbersome, time consuming, and laborious. For a class of linear network topology, a semi-autonomous coordinate configuration technology of base stations is designed, which refers to three conceptions of segmentation, virtual triangle, and bidirectional calculation. It consists of two stages in every segment: Forward and backward. In the forward stage, it utilizes the manual coordinate setup method to deal with the foremost two base stations, and then the remaining base stations autonomously calculate their coordinates by building the virtual triangle train. In the backward stage, the reverse operation is performed, but the foremost two base stations of the next segment should be used as the head. In the last segment, the last two base stations should be used as the head. Integrating forward and backward data, the base stations could improve their location accuracy. It is shown that our algorithm is feasible and practical in simulation results and can dramatically reduce the system configuration time. In addition, the error and maximum base station number for one segment caused by our algorithm are discussed theoretically.



2013 ◽  
Vol 319 ◽  
pp. 517-522
Author(s):  
Xie Yuan ◽  
Zhong Liang Deng ◽  
Yu Zhang

Location based service (LBS) is more and more important nowadays. Assisted with GNSS, Base Station Positioning System (BSPS) can offer seamless outdoor & indoor positioning. The fading channel causes problems in signal acquisition. In this paper, a new method of RAM-based frequency acquisition is introduced, which can acquire the residual carrier frequency in fading channel accurately.





2018 ◽  
Vol 39 (4) ◽  
pp. 437-447 ◽  
Author(s):  
Zichun Le ◽  
Xianyu Zeng ◽  
Minglei Fu

Abstract Visible light communication (VLC) is an emerging optical communication technology, and indoor positioning of moving target devices is one of most important issues in the VLC system. In this study, we focused on LED base station location planning to improve the accuracy of the positioning method based on the received signal strength intensity (RSS) and the Kalman filter (KF). We developed a new base station location-planning scheme called equilateral triangle distribution. We proved theoretically that the equilateral triangle distribution scheme reduced the positioning error area when compared with the rectangular distribution scheme. The simulation results showed that the measuring error of the equilateral triangle distribution method using KF was less than 5 cm, even when the receiver was located at the boundary of the room. Our method verified that the VLC indoor positioning accuracy can be improved when LED base stations are distributed according to our equilateral triangle distribution scheme.



2021 ◽  
Vol 10 (10) ◽  
pp. 669
Author(s):  
Dayu Cheng ◽  
Guo Yue ◽  
Tao Pei ◽  
Mingbo Wu

Indoor positioning data reflects human mobility in indoor spaces. Revealing patterns of indoor trajectories may help us understand human indoor mobility. Clustering methods, which are based on the measurement of similarity between trajectories, are important tools for identifying those patterns. However, due to the specific characteristics of indoor trajectory data, it is difficult for clustering methods to measure the similarity between trajectories. These characteristics are manifested in two aspects. The first is that the nodes of trajectories may have clear semantic attributes; for example, in a shopping mall, the node of a trajectory may contain information such as the store type and visit duration time, which may imply a customer’s interest in certain brands. The semantic information can only be obtained when the position precision is sufficiently high so that the relationship between the customer and the store can be determined, which is difficult to realize for outdoor positioning, either using GPS or mobile base station, due to the relatively large positioning error. If the tendencies of customers are to be considered, the similarity of geometrical morphology does not reflect the real similarity between trajectories. The second characteristic is the complex spatial shapes of indoor trajectory caused by indoor environments, which include elements such as closed spaces, multiple obstacles and longitudinal extensions. To deal with these challenges caused by indoor trajectories, in this article we proposed a new method called E-DBSCAN, which extended DBSCAN to trajectory clustering of indoor positioning data. First, the indoor location data were transformed into a sequence of residence points with rich semantic information, such as the type of store customer visited, stay time and spatial location of store. Second, a Weighted Edit Distance algorithm was proposed to measure the similarity of the trajectories. Then, an experiment was conducted to verify the correctness of E-DBSCAN using five days of positioning data in a shopping mall, and five shopping behavior patterns were identified and potential explanations were proposed. In addition, a comparison was conducted among E-DBSCAN, the k-means and DBSCAN algorithms. The experimental results showed that the proposed method can discover customers’ behavioral pattern in indoor environments effectively.



Author(s):  
Xiao-min Yu ◽  
Hui-qiang Wang ◽  
Hong-wu Lv ◽  
Xiu-bing Liu ◽  
Jin-qiu Wu

AbstractThe indoor scene has the characteristics of complexity and Non-Line of Sight (NLOS). Therefore, in the application of cellular network positioning, the layout of the base station has a significant influence on the positioning accuracy. In three-dimensional indoor positioning, the layout of the base station only focuses on the network capacity and the quality of positioning signal. At present, the influence of the coverage and positioning accuracy has not been considered. Therefore, a network element layout optimization algorithm based on improved Adaptive Simulated Annealing and Genetic Algorithm (ASA-GA) is proposed in this paper. Firstly, a three-dimensional positioning signal coverage model and a base station layout model are established. Then, the ASA-GA algorithm is proposed for optimizing the base station layout scheme. Experimental results show that the proposed ASA-GA algorithm has a faster convergence speed, which is 16.7% higher than the AG-AC (Adaptive Genetic Combining Ant Colony) algorithm. It takes about 25 generations to achieve full coverage. At the same time, the proposed algorithm has better coverage capability. After optimization of the layout of the network element, the effective coverage rate is increased from 89.77 to 100% and the average location error decreased from 2.874 to 0.983 m, which is about 16% lower than the AG-AC algorithm and 22% lower than the AGA (Adaptive Genetic Algorithm) algorithm.



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