scholarly journals Experimental Radio Indoor Positioning Systems Based on Round-Trip Time Measurement

10.5772/8724 ◽  
2010 ◽  
Author(s):  
Alessio De ◽  
Antonio Moschitta ◽  
Peter Handel ◽  
Paolo Carbone
2014 ◽  
Vol E97.B (10) ◽  
pp. 2145-2156
Author(s):  
Xinjie GUAN ◽  
Xili WAN ◽  
Ryoichi KAWAHARA ◽  
Hiroshi SAITO

2021 ◽  
pp. 101416
Author(s):  
Omar Hashem ◽  
Khaled A. Harras ◽  
Moustafa Youssef

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7261
Author(s):  
Hajime Ando ◽  
Shingo Sekoguchi ◽  
Kazunori Ikegami ◽  
Hidetaka Yoshitake ◽  
Hiroka Baba ◽  
...  

Monitoring of personal exposure to hazardous substances has garnered increasing attention over the past few years. However, no straightforward and exact indoor positioning technique has been available until the recent discovery of Wi-Fi round trip time (Wi-Fi RTT). In this study, we investigated the possibility of using a combination of Wi-Fi RTT for indoor positioning and a wearable particle monitor (WPM) to observe dust concentration during walking in a simulated factory. Ultrasonic humidifiers were used to spray sodium chloride solution inside the factory. The measurements were recorded three times on different routes (Experiments A, B, and C). The error percentages, i.e., measurements that were outside the expected measurement area, were 7% (49 s/700 s) in Experiment A, 2.3% (15 s/660 s) in Experiment B, and 7.8% (50 s/645 s) in Experiment C. The dust measurements were also recorded without any obstruction. A heat map was created based on the results from both measured values. Wi-Fi RTT proved useful for computing the indoor position with high accuracy, suggesting the applicability of the proposed methodology for occupational health monitoring.


2021 ◽  
Author(s):  
Paolo Carbone

<div><div><div><p>In this paper, a technique for modeling propagation of Ultra Wide Band (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on Round Trip Time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an Additive White Gaussian Noise Channel, and detected using a threshold based receiver, it is shown that RTT measurements may be affected by a non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of a RTT based positioning system are investigated. To this aim, a classical Least Square, an extended Kalman Filter and a Particle Filter are compared when used to detect a slowly moving target in presence of the modeled noise. It is shown that, in a realistic indoor environment, the Particle Filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.</p></div></div></div>


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