Enhanced Out of Boundary UWB Based Localization for Industrial Digital Twins

By combining data-driven decision-making, and real-time analysis, Industry 4.0 is transforming industrial processes, including manufacturing, logistics, healthcare, and energy. The Industrial Internet of Things (IIoT), Big Data analytics, and reliable wireless networks like Ultra-Wideband (UWB) are some of the key technologies behind this change. Digital Twin creates big Industry 4.0 systems' virtual clones of the physical world in the digital environment and enables real-time monitoring, simulation, and predictive maintenance. UWB allows for precise localization, which is important for applications that need precise asset and human tracking in Digital Twin Applications. Time Difference of Arrival (TDoA) is one of the most popular UWB algorithms. TDoA requires only one signal to estimate the TX device location. When combined with UWB-based TDoA localization, Digital Twin simplifies precise tracking of asset positions and provides synchronization between digital models and the physical world. This work focuses on enhancing TDoA-based position estimation and optimizing the computational cost for situations in which transmitters are outside receiver bounds. Techniques like error weighting and hyperbola selection are applied to improve accuracy and provide faster localization solutions in Digital Twin systems.