Characterisation of electromagnetic properties in iron-mine production tunnels

Ferrer-Coll, Javier; Ängskog, Per; Chilo, José; Stenumgaard, Peter

doi:10.1049/el.2011.3133

Cited by 9 publications

(11 citation statements)

References 3 publications

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“…Numerous papers have investigated the propagation in 'non-subway' tunnel environments: [2][3][4] focus on the high-speed railway and highway tunnels. These tunnels are usually of large transverse dimensions, which is quite different from the subway condition, and the measurements in [2][3][4] were not conducted by a real moving subway train therefore the effect of the train was not considered in the analysis, so that the results cannot provide reliable guidelines for subway tunnel communications; [5][6][7][8] aim at the underground mine tunnels. These tunnels are usually very small and only allow the human's mobility.…”

Section: Introductionmentioning

confidence: 99%

Propagation channel measurements and analysis at 2.4 GHz in subway tunnels

Zhang

et al. 2013

IET Microwaves, Antennas & Propagation

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The reliability of communication systems in a subway tunnel requires an absolute understanding of the propagation channel in this environment. From an insightful look at the subway channel and especially when compared with the other underground propagation environments such as mines, roads and railway tunnels, an important feature of the subway tunnel is the existence of stations in the tunnel. These stations cause extra reflection in the channel and also increase the delay spread observed. Although this effect has been largely neglected in available propagation channel literature, this is an important concept that ought to be explored. In this work, the authors present channel measurements conducted close to a station in a subway tunnel at 2.4 GHz, using a self‐developed frequency domain channel sounder. To aid the authors analysis, three typical propagation regions are defined: line‐of‐sight (LOS), non‐LOS and far‐LOS, and also use a larger observation delay window to investigate the long delay clusters caused by the existence of stations in subway tunnel. From the analysis of the power delay profile (PDP), root‐mean‐square delay spread and scattering function in the three propagation regions, the authors have been able to infer a long delay cluster of about 2 µs, which the authors attributed to multipath propagation of signal along the tunnel and reflections in the station. The Saleh–Valenzuela model is used to characterise the long clustering phenomenon observed in the PDP. The results show that the time spreading in subway tunnel is more significant because of the station compared with other underground tunnels, which leads to substantial signal distortion.

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Section: Introductionmentioning

confidence: 99%

Propagation channel measurements and analysis at 2.4 GHz in subway tunnels

Zhang

et al. 2013

IET Microwaves, Antennas & Propagation

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“…In [13], the authors proposed a multimode model for predicting the received power and the PDP in tunnels with pillars. The analysis of measurements performed in wide and narrow iron-mine tunnels [14] show a small delay spread even in NLOS scenarios. The work in [15] analyzed the channel of an underground gold mine, and found that the RMS delay spread is decreasing with distance.…”

Section: A Overview Of Measurements Campaignsmentioning

confidence: 96%

“…Multipath propagation has been studied and characterized in a multitude of environments, such as residential buildings, indoor offices and mines. The work performed in [6] proposes statistical models for estimating the root-mean-square (RMS) delay spread, path-loss and other relevant propagation [10] 1.89 0.5 298 Paper mill [10] 1.89 0.5 23 Subway tunnel [11] 2.4 0.1 159-234 Road tunnel [12] 5.2 0.1 20-100 Mine tunnel [13] 1 0.2 20-50 Mine tunnel [14] 2.4 0.5 14 Mine tunnel [15] 2.4 0.2 27.4 Mine tunnel [16] 2.4/5.8 0.2 1-15 Mine tunnel [17] 3.5 3 11-29 Mine tunnel [18] 2.4 0.2 1.7 LiU tunnel 3.5 2 3-16…”

Section: A Overview Of Measurements Campaignsmentioning

confidence: 99%

Measurement Analysis and Channel Modeling for TOA-Based Ranging in Tunnels

Savic

Ferrer-Coll

Ängskog

et al. 2015

IEEE Trans. Wireless Commun.

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Abstract-A robust and accurate positioning solution is required to increase the safety in GPS-denied environments. Although there is a lot of available research in this area, little has been done for confined environments such as tunnels. Therefore, we organized a measurement campaign in a basement tunnel of Linköping university, in which we obtained ultra-wideband (UWB) complex impulse responses for line-of-sight (LOS), and three non-LOS (NLOS) scenarios. This paper is focused on timeof-arrival (TOA) ranging since this technique can provide the most accurate range estimates, which are required for rangebased positioning. We describe the measurement setup and procedure, select the threshold for TOA estimation, analyze the channel propagation parameters obtained from the power delay profile (PDP), and provide statistical model for ranging. According to our results, the rise-time should be used for NLOS identification, and the maximum excess delay should be used for NLOS error mitigation. However, the NLOS condition cannot be perfectly determined, so the distance likelihood has to be represented in a Gaussian mixture form. We also compared these results with measurements from a mine tunnel, and found a similar behavior.

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“…Exactly there the most negative effects of "locomotive -wagon" collisions manifest themselves [10]. Analysis of the dynamic forces occurring in couplings during train acceleration and deceleration is presented in work [11], but the influence of the system parameters on emergence of oscillatory processes taking place in it was not shown. The conditions of underground hauling make it practically impossible to manage these works in a manual way.…”

Section: Development Of a System To Control The Motion Of Electric Trmentioning

confidence: 99%

“…From an operational point of view, the operations of wagon moving should be carried out in a minimum time which will increase productivity. Thus, it is necessary to synthesize an electric train control algorithm which is optimal for speed of operation [11]. The equation of the train movement is described by the differential equation:…”

Section: Fig 2 Block Diagram Of the Algorithm For Eliminating Oscilmentioning

confidence: 99%