Improved Observation Interval Bounding for Multi-GNSS Integrity Monitoring in Urban Navigation

Reference trajectory in the i.c.sens measurement compaign

Abstract

Talk at ION GNSS+ 2021, awarded best presentation of the track.

Date
Sep 24, 2021 1:00 PM — 2:00 PM
Location
Virtual, St. Louis, MO, US

Integrity monitoring is of great importance for Global Navigation Satellite Systems (GNSS) applications. Unlike classical approaches based on probabilistic assumptions, the alternative interval-based integrity approach depends on deterministic interval bounds as inputs. Different from a quadratic variance propagation, the interval approach has intrinsically a linear uncertainty propagation which is adequate to describe remaining systematic uncertainty.

In order to properly characterize all ranging error sources and determine the improved observation interval bounds, a processing scheme is proposed in this contribution. We validated for a first time how the sensitivity analysis is feasible to determine uncertainty intervals for residual ionospheric errors and residual tropospheric errors, taking advantage of long-term statistics against reference data. Transforming the navigation problem into a convex optimization problem, the interval bounds are propagated from the range domain to the position domain.

We implemented this strategy for multi-GNSS positioning in an experiment with static data from International GNSS Service (IGS) station Potsdam (POTS) and an experiment with kinematic data from a measurement campaign conducted in the urban area of Hannover, Germany, on August 26, 2020.

Jingyao Su
Jingyao Su
Doctoral researcher of GNSS navigation

My research interests include GNSS navigation, integrity monitoring and uncertainty modeling with interval mathematics.