Abstract
Indoor positioning techniques are being considered for use within team sports where players are tracked and recorded providing coaching assistance. While Global Positioning System (GPS) is the de facto standard employed to estimate the location of players, this is unsuitable for accurate indoor positioning due to roof and wall signal obstruction. Over a dozen techniques have been suggested for wireless indoor positioning of static and/or moving objects with improved methods for limiting the position estimation errors. For those indoor techniques that rely on radio frequency (RF) signal propagation, propagation statistics are useful in determining path loss and signal degradation. This static indoor propagation knowledge is critical in the design of wireless indoor positioning systems and ultimately the accuracy of the position estimation. Signal path propagation losses and variations produced from shadowing, multipath, fading, scattering or diffraction from objects can hinder the designer's efforts to provide a reliable and accurate positioning system. However, sporting indoor environments generally have an open floor area where play is conducted free from objects apart from the players themselves. At the elite sporting level these indoor play areas are designed and constructed under international specifications. Consequently, static wireless RF signal propagation knowledge obtained from one of these commonly built play areas is applicable to hundreds of other venues around the world. Many of these indoor sporting areas are used for a variety of sports, for example, basketball, volleyball, indoor cricket, indoor soccer, netball and handball. A player positioning installation could potentially be used for all of these sports. This paper reports the wireless RF signal propagation of a 2.4GHz waist mounted beacon for an indoor sporting venue ‘play area’, which has been designed to international standards. A basketball court constructed of highly polished wood was chosen as the sample ‘play area’. Propagation models are discussed and comparisons between predicted and measured results demonstrate the validity of the technique.
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