Experimental Evaluation of UWB Indoor Positioning for Sport Postures

Abstract

Radio frequency (RF)-based indoor positioning systems (IPSs) use wireless technologies (including Wi-Fi, Zigbee, Bluetooth, and ultra-wide band (UWB)) to estimate the location of persons in areas where no Global Positioning System (GPS) reception is available, for example in indoor stadiums or sports halls. Of the above-mentioned forms of radio frequency (RF) technology, UWB is considered one of the most accurate approaches because it can provide positioning estimates with centimeter-level accuracy. However, it is not yet known whether UWB can also offer such accurate position estimates during strenuous dynamic activities in which moves are characterized by fast changes in direction and velocity. To answer this question, this paper investigates the capabilities of UWB indoor localization systems for tracking athletes during their complex (and most of the time unpredictable) movements. To this end, we analyze the impact of on-body tag placement locations and human movement patterns on localization accuracy and communication reliability. Moreover, two localization algorithms (particle filter and Kalman filter) with different optimizations (bias removal, non-line-of-sight (NLoS) detection, and path determination) are implemented. It is shown that although the optimal choice of optimization depends on the type of movement patterns, some of the improvements can reduce the localization error by up to 31%. Overall, depending on the selected optimization and on-body tag placement, our algorithms show good results in terms of positioning accuracy, with average errors in position estimates of 20 cm. This makes UWB a suitable approach for tracking dynamic athletic activities.

A decision tree‐based NLOS detection method for the UWB indoor location tracking accuracy improvement

“…The common localization method is based on the trilateration algorithm . This algorithm requires three or more reference points to determine the location of an object.…”

“…The common localization method is based on the trilateration algorithm. [8][9][10][11][12][13][14] This algorithm requires three or more reference points to determine the location of an object. In the study of Musa et al, 15 we proposed another localization method, a dulateration-based indoor location tracking (Dilacak) algorithm, which used to track a moving object using only two reference points.…”

Foldable All‐Textile Cavity‐Backed Slot Antennas for Personal UWB Localization

“…This low power use is particularly favorable for body-worn systems considering their often limited availability of power . Furthermore, the high available bandwidth enables impulse radio ultra-wideband (IR-UWB) systems to use very narrow time-domain pulses, which allow for ranging at centimeter-scale accuracy (Alarifi et al, 2016;Ridolfi et al, 2018) with a high immunity against multipath fading (Kshetrimayum, 2009). Examples of applications include cyclist positioning systems using the Decawave DW1000 IC (Minne et al, 2019), systems for respiration and heartbeat monitoring (Shen et al, 2018), drone localization (Lazzari et al, 2017), and breathing detection of victims buried under building rubble (Lv et al, 2014).…”

Research on Wavelet Threshold Denoising Method for UWB Tunnel Personnel Motion Location

“…Savic et al [15] studied non-line-of-sight recognition based on the UWB positioning system in tunnels by analyzing channel propagation parameters. Matteo Ridol et al [16] analyzed the effects of tag placement and human motion patterns on positioning accuracy and communication reliability and designed two algorithms, particle filter and Kalman filter, to further improve the accuracy of the localization algorithm.…”