Abstract
Ultra-wideband (UWB) and WiFi technologies have been widely proposed for the implementation of accurate and scalable indoor positioning systems (IPSs). Among different approaches, fingerprinting appears particularly suitable for WiFi IPSs and was also proposed for UWB IPSs, in order to cope with the decrease in accuracy of time of arrival (ToA)-based lateration schemes in the case of severe multipath and non-line-of-sight (NLoS) environments. However, so far, the two technologies have been analyzed under very different assumptions, and no fair performance comparison has been carried out. This paper fills this gap by comparing UWB- and WiFi-based fingerprinting under similar settings and scenarios by computer simulations. Two different k-nearest neighbor (kNN) algorithms are considered in the comparison: a traditional fixed k algorithm, and a novel dynamic k algorithm capable of operating on fingerprints composed of multiple location-dependent features extracted from the channel impulse response (CIR), typically made available by UWB hardware. The results show that UWB and WiFi technologies lead to a similar accuracy when a traditional algorithm using a single feature is adopted; when used in combination with the proposed dynamic k algorithm operating on channel energy and delay spread, UWB outperforms WiFi, providing higher accuracy and more degrees of freedom in the design of the system architecture.
Highlights
Information on the position of wireless devices may help the implementation of next-generation communication systems, infrastructures and services [1,2]
Because the fixed k-nearest neighbor (kNN) algorithm does not support the use of multifeature fingerprints, in the analysis presented in this subsection, WiFi was compared with UWB using either of the two features, leading to three different systems: (a) WiFi; (b) UWB-energy, only using channel impulse response (CIR) energy; and (c) UWB-root-mean-square delay spread (RMS-DS), only using CIR RMS-DS
A comparison of WiFi- and UWB-based fingerprinting indoor positioning systems (IPSs) was carried out, in order to verify whether UWB technology can still lead to a higher accuracy with respect to WiFi when operating in scenarios characterized by the same anchor nodes (ANs) and reference node (RN) densities
Summary
Information on the position of wireless devices may help the implementation of next-generation communication systems, infrastructures and services [1,2]. UWB IPSs are based on triangulation principles applied to dedicated infrastructures formed by anchor nodes (ANs). Within these systems, the first positioning phase is referred to as ranging, and it estimates the distances between each AN and a device in the unknown position, referred to in the following as a target node (TN), through either lateration techniques, such as time of arrival (ToA) and time difference of arrival (TDoA), or through the received signal strength (RSS); the estimate of the TN position is obtained by exploiting the ranging phase results, through either geometric or linear and non-linear least squares minimization approaches [4]. It is demonstrated that these schemes are highly accurate when line-of-sight (LoS) and perfect time synchronization conditions are verified between ANs and the TN; several factors, such as (a) direct path excess-delay/blockage
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