M-SHOW: A SYSTEM FOR ACCURATE POSITION ESTIMATION IN MULTI-FLOOR BUILDINGS

2018 ◽  
Vol 246 ◽  
pp. 03024
Author(s):  
Pengfei Wang ◽  
Weidong Li ◽  
Xinping Wang ◽  
Xianwu Chu

A train positioning method based on GPS and digital rail line matching is proposed. Firstly, the digital track line is generated based on the fitting and interpolation algorithm of train track line. And then the GPS data are corrected by the track line positioning correction method, and the more accurate position estimation of the train is obtained. Finally, the data track line is simulated and analyzed with some measured data from Harbin to Qigihar track line. The analysis results show that cubic spline curve is better than cubic B-spline curve on the establishment of digital track map.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Juraj Machaj ◽  
Peter Brida ◽  
Jozef Benikovsky

Recently positioning services are getting more attention not only within research community but also from service providers. From the service providers point of view positioning service that will be able to work seamlessly in all environments, for example, indoor, dense urban, and rural, has a huge potential to open new markets. However, such system does not only need to provide accurate position estimates but have to be scalable and resistant to fake positioning requests. In the previous works we have proposed a modular system, which is able to provide seamless positioning in various environments. The system automatically selects optimal positioning module based on available radio signals. The system currently consists of three positioning modules—GPS, GSM based positioning, and Wi-Fi based positioning. In this paper we will propose algorithm which will reduce time needed for position estimation and thus allow higher scalability of the modular system and thus allow providing positioning services to higher amount of users. Such improvement is extremely important, for real world application where large number of users will require position estimates, since positioning error is affected by response time of the positioning server.


Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1064 ◽  
Author(s):  
Arne Niitsoo ◽  
Thorsten Edelhäußer ◽  
Ernst Eberlein ◽  
Niels Hadaschik ◽  
Christopher Mutschler

Radio-based locating systems allow for a robust and continuous tracking in industrial environments and are a key enabler for the digitalization of processes in many areas such as production, manufacturing, and warehouse management. Time difference of arrival (TDoA) systems estimate the time-of-flight (ToF) of radio burst signals with a set of synchronized antennas from which they trilaterate accurate position estimates of mobile tags. However, in industrial environments where multipath propagation is predominant it is difficult to extract the correct ToF of the signal. This article shows how deep learning (DL) can be used to estimate the position of mobile objects directly from the raw channel impulse responses (CIR) extracted at the receivers. Our experiments show that our DL-based position estimation not only works well under harsh multipath propagation but also outperforms state-of-the-art approaches in line-of-sight situations.


2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Jae-Hoon Kim ◽  
Kyoung Sik Min ◽  
Woon-Young Yeo

The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 56359-56370 ◽  
Author(s):  
Zhiliang Zhu ◽  
Yingli Wen ◽  
Zhengjiang Zhang ◽  
Zhengbing Yan ◽  
Shipei Huang ◽  
...  

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