Abstract
This paper analyzes the performance of an ultra-wideband (UWB) wireless network system for mobile asset tracking at a dynamic construction site. Static and dynamic error tests were performed on a commercial UWB system in different building spaces including open/closed spaces, steel/wood framed construction sites, and a closed office area. All tests were carried out with an untethered UWB configuration for more flexible deployment of the UWB system at construction sites. Statistical approaches including regression analysis, outlier detection, and Kalman filtering were used to build an error model. The research found that each site has a unique pattern of producing errors caused by various types of interference, e.g., electromagnetic interference, multi-path propagation, fading and scattering of signals. Approximately 25% of the errors were reduced by using the proposed error modeling process. The paper concludes that a statistically developed error model process can significantly reduce random errors and improve position accuracy for indoor mobile asset tracking applications in construction.
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