Cooperative Differential GNSS Positioning: Estimators and Bounds

TL;DR

This paper explores how large-scale user cooperation in Differential GNSS can mitigate reference-station noise, improving positioning accuracy especially with mixed-quality reference infrastructure, through a unified estimation framework and theoretical analysis.

Contribution

It introduces a unified estimation framework for cooperative DGNSS and derives Fisher information bounds, revealing how cooperation can restore accuracy in noisy reference scenarios.

Findings

Cooperation improves accuracy in mixed-quality reference environments.

Theoretical bounds show asymptotic accuracy restoration with large networks.

Simulations confirm the effectiveness of cooperative strategies.

Abstract

In Differential GNSS (DGNSS) positioning, differencing measurements between a user and a reference station suppresses common-mode errors but also introduces reference-station noise, which fundamentally limits accuracy. This limitation is minor for high-grade stations but becomes significant when using reference infrastructure of mixed quality. This paper investigates how large-scale user cooperation can mitigate the impact of reference-station noise in conventional (non-cooperative) DGNSS systems. We develop a unified estimation framework for cooperative DGNSS (C-DGNSS) and cooperative real-time kinematic (C-RTK) positioning, and derive parameterized expressions for their Fisher information matrices as functions of network size, satellite geometry, and reference-station noise. This formulation enables theoretical analysis of estimation performance, identifying regimes where cooperation asymptotically restores the accuracy of DGNSS with an ideal (noise-free) reference. Simulations validate these theoretical findings.