  Precise positioning and navigation information has been increasingly
important with the development of the consumer electronics market. Due to some
deficits of Global Navigation Satellite System (GNSS), such as susceptible to
interferences, integrating of GNSS with additional alternative sensors is a
promising approach to overcome the performance limitations of GNSS-based
localization systems. Ultra-Wideband (UWB) can be used to enhance GNSS in
constructing an integrated localization system. However, most low-cost UWB
devices lack a hardware-level time synchronization feature, which necessitates
the estimation and compensation of the time-offset in the tightly coupled
GNSS/UWB integration. Given the flexibility of probabilistic graphical models,
the time-offset can be modeled as an invariant constant in the discretization
of the continuous model. This work proposes a novel architecture in which
Factor Graph Optimization (FGO) is hybrid with Extend Kalman Filter (EKF) for
tightly coupled GNSS/UWB integration with online Temporal calibration (FE-GUT).
FGO is utilized to precisely estimate the time-offset, while EKF provides
initailization for the new factors and performs time-offset compensation.
Simulation-based experiments validate the integrated localization performance
of FE-GUT. In a four-wheeled robot scenario, the results demonstrate that,
compared to EKF, FE-GUT can improve horizontal and vertical localization
accuracy by 58.59\% and 34.80\%, respectively, while the time-offset estimation
accuracy is improved by 76.80\%. All the source codes and datasets can be
gotten via https://github.com/zhaoqj23/FE-GUT/.
