Low-Cost Inertial Aiding for Deep-Urban Tightly-Coupled Multi-Antenna Precise GNSS
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by
James E. Yoder, Todd E. Humphreys
2022
Abstract
A vehicular pose estimation technique is presented that tightly couples
multi-antenna carrier-phase differential GNSS (CDGNSS) with a low-cost MEMS
inertial sensor and vehicle dynamics constraints. This work is the first to
explore the use of consumer-grade inertial sensors for tightly-coupled urban
CDGNSS, and first to explore the tightly-coupled combination of multi-antenna
CDGNSS and inertial sensing (of any quality) for urban navigation. An unscented
linearization permits ambiguity resolution using traditional integer least
squares while both implicitly enforcing known-baseline-length constraints and
exploiting the multi-baseline problem's inter-baseline correlations. A novel
false fix detection and recovery technique is developed to mitigate the effect
of conditioning the filter state on incorrect integers. When evaluated on the
publicly-available TEX-CUP urban positioning dataset, the proposed technique
achieves, with consumer- and industrial-grade inertial sensors, respectively, a
96.6% and 97.5% integer fix availability, and 12.0 cm and 10.1 cm overall (fix
and float) 95th percentile horizontal positioning error.
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