An analysis of the effects of different network-based ionosphere stimation models on rover positioning accuracy

Dorota A. Grejner-Brzezinska, Pawel Wielgosz, Israel Kashani, Dru A. Smith, Paul S. J. Spencer, Douglas S. Robertson, Gerald L. Mader

National Geodetic Survey – NGS.
The Ohio State University, SPIN LAB, 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43210-1275; Israel Institute of Technology – Technion.
The Ohio State University, SPIN LAB, 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43210-1275The Ohio State University, SPIN LAB, 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43210-1275.
The Ohio State University, SPIN LAB, 470 Hitchcock Hall, 2070 Neil Ave., Columbus; University of Warmia and Mazury – UWM.

DOI:                 

Abstract

The primary objective of this paper is to test several methods of modeling the ionospheric corrections derived from a reference GPS network, and to study the impact of the models’ accuracy on the user positioning results. The five ionospheric models that are discussed here are: (1) network RTK (NR) carrier phase-based model — MPGPS-NR, (2) absolute, smoothed pseudorange-based model — MPGPS-P4, (3) IGS Global Ionosphere Model — GIM, (4) absolute model based on undifferenced dual-frequency ambiguous carrier phase data — ICON, and (5) carrier phase-based data assimilation method — MAGIC. Methods 1–4 assume that the ionosphere is an infinitesimal single layer, while method (5) considers the ionosphere as a 3D medium.The test data set was collected at the Ohio Continuously Operating Reference Stations (CORS) network on August 31, 2003. A 24-hour data set, representing moderate ionospheric conditions (maximum Kp = 2o), was processed. The ionospheric reference “truth” in doubledifference (DD) form was generated from the dualfrequency carrier phase data for two selected baselines, ~60 and ~100 km long, where one station was considered as a user receiver at an unknown location (simulated rover). The five ionospheric models were used to generate the DD ionospheric corrections for the rover, and were compared to the reference “truth.” The quality statistics were generated and discussed. Examples of instantaneous ambiguity resolution and RTK positioning are presented, together with the accuracy requirements for the ionospheric corrections, to assure integer ambiguity fixing.

Keywords

Network-based RTK, ionospheric models, ambiguity resolution.

Conflicts of Interest

The authors declare no conflicts of interest.

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