Investigation of wireless tracking performance in the tunnel-like environment with particle filter

Abstract

When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added. When the basic nonlinear filtering problem for dynamic systems is considered, in such case, the particle filter is one of the suitable methods that has perhaps become one of the most commonly used methods in recent years. Positioning or localization falls under such a nonlinear filtering problem. Positioning is a matter of interest for both domestic and industrial application, due to its potential use in wide range of context-aware services that it can enable by leveraging the Internet of Things approach. However, in areas where GPS signals are not available such as underground tunnel roadways, where the localization is done mostly using radio beacons. This study mathematically simulates tracking operation in such a tunnel-like situation and studied the position estimation by the particle filter. From the results, we were able to visualize how varying different configuration parameters affect the estimation accuracies and also get an idea of worst-case estimates by seeing its standard deviation of estimated positions for different instances of repeated experiments. And our results also confirmed that deploying additional beacons have a contribution to the improvement in error tolerance. However, the improvements are significantly notable only around the point where beacon has been added.

Anti-seismic Effect of the Shock Absorption Layer in Tunnel

“…To improve the effect of shock absorption, the damping material should have greater damping values. In this study, the variables 11=0.05, =0.6, =1.4, r2=0.05~1.5, k1=4.510 9 Pa, and k3=310 10 Pa were determined, so 1 is calculated according to the stiffness of the surrounding rock. The frequency ratio  is 0.05, 0.1, 0.5, 1.0, 2.0, 3.0, 4.0, 6.0, 8.0 and 10.0.…”

“…Over the years, the problems of tunnel construction have been studied by many researchers, and many studies have been published [5][6][7][8][9]. Okamoto and Choshiro [10] pointed out that great developments have been made through research regarding the numerical analysis of the tunnel dynamic response at home and abroad.…”

High-precision positioning of mine personnel based on wireless pulse technology

“…Simulation results show that the algorithm improves positioning accuracy. Fujiwara (2007), Mizugaki et al (2007), Fujiwara et al (2008), Halber and Chakravarty (2018) studied a time of arrival (TOA)/time difference of arrival (TDOA) hybrid relative positioning system using ultra-wideband impulse radio (UWB-IR) technology and evaluated the system performance for various distances between base stations through computer simulation and experiment; the positioning error of the system was as low as 22 cm [13–16]. Kim (2009) and Wang et al (2010) summarized the excitation, principle, and detailed mathematical background of two-way ranging (TWR) and proposed a new ranging algorithm for an asynchronous positioning system, which reduced the number of data packets used in the ranging process and improved the range accuracy [17–18].…”

“…Comparative analysis reveals that the above methods have large error in positioning and the positioning clock has a large delay [23]. Awad et al (2007) proposed a method that can only achieve a positioning accuracy of 50 cm even in the region of 3.5 x 4.5 m. Although the positioning methods proposed in the literatures has an accuracy of 22 cm, the positioning delay is large and the system layout is more complicated [12–16]. The accuracy of the two-way ranging method depends on the clock drift of the device.…”

A Proposed Use of Kalman Gains Behavior of Navigation Measurements for the Sensor Fault Detection in Quadcopter

“…Looking back in the past papers devoted to sensor fault detection have used Kalman filter to estimate the output to be used by detection process [5][6][7][8][9]. The basic idea behind the observer or filter-based approach was to estimate the outputs of the system from the measurements with a use of either Luenberger observer(s) in a deterministic setting or Kalman filter(s) in a stochastic setting.…”