Low-Cost Inertial Aiding for Deep-Urban Tightly Coupled Multi-Antenna Precise GNSS

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 dynamic 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 data set, the proposed technique achieves, with consumer- and industrial-grade inertial sensors, respectively, a 96.6% and 97.5% integer fix availability, and a 12.0-cm and 10.1-cm overall (fix and float) 95th percentile horizontal positioning error.