Kavli Affiliate: Wei Gao
| First 5 Authors: Jihong Huang, Jihong Huang, , ,
| Summary:
Direct Position Estimation (DPE) is a method that directly estimate position,
velocity, and time (PVT) information from cross ambiguity function (CAF) of the
GNSS signals, significantly enhancing receiver robustness in urban
environments. However, there is still a lack of theoretical characterization on
multipath errors in the context of DPE theory. Geometric observations highlight
the unique characteristics of DPE errors stemming from multipath and thermal
noise as estimation bias and variance respectively. Expanding upon the
theoretical framework of DPE noise variance through geometric analysis, this
paper focuses on a geometric representation of multipath errors by quantifying
the deviations in CAF and PVT solutions caused by off-centering bias relative
to the azimuth and elevation angles. A satellite circular multipath bias (SCMB)
model is introduced, amalgamating CAF and PVT errors from multiple satellite
channels. The boundaries for maximum or minimum PVT bias are established
through discussions encompassing various multipath conditions. The correctness
of the multipath geometrical portrait is confirmed through both Monte Carlo
simulations and urban canyon tests. The findings indicate that the maximum PVT
bias depends on the largest multipath errors observed across various satellite
channels. Additionally, the PVT bias increases with satellite elevation angles,
influenced by the CAF multipath bias projection. This serves as a reference for
selecting DPE satellites from a geometric standpoint, underscoring the
importance of choosing a balanced combination of high and low elevation angles
to achieve an optimal satellite geometry configuration.
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