  The recently proposed factor graph optimization (FGO) is adopted to integrate
GNSS/INS attracted lots of attention and improved the performance over the
existing EKF-based GNSS/INS integrations. However, a comprehensive comparison
of those two GNSS/INS integration schemes in the urban canyon is not available.
Moreover, the performance of the FGO-based GNSS/INS integration rely heavily on
the size of the window of optimization. Effectively tuning the window size is
still an open question. To fill this gap, this paper evaluates both loosely and
tightly-coupled integrations using both EKF and FGO via the challenging dataset
collected in the urban canyon. The detailed analysis of the results for the
advantages of the FGO is also given in this paper by degenerating the FGO-based
estimator to an EKF like estimator. More importantly, we analyze the effects of
window size against the performance of FGO, by considering both the GNSS
pseudorange error distribution and environmental conditions.
