An improved approach to model ionospheric delays for single-frequency Precise Point Positioning

• Published in: Advances in space research Vol. 49; no. 12; pp. 1698 - 1708
• Main Authors: Shi, Chuang, Gu, Shengfeng, Lou, Yidong, Ge, Maorong
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15-06-2012; Elsevier
• Subjects: Astronomy; Earth, ocean, space; Exact sciences and technology; External geophysics; Ionospheric delay correction; Ionospheric delay representation; Low-cost single-frequency receiver; Precise Point Positioning; Ionospheric delay correction; Ionospheric delay representation; Precise Point Positioning; Low-cost single-frequency receiver; Validation; Stochastic processes; Space remote sensing; Satellite observation; Calibration; Space research; Spatial variation; Empirical model; Time variation; Convergence; Mitigation; Deterministic model; Database; Corrections
• ISSN: 0273-1177; 1879-1948
• DOI: 10.1016/j.asr.2012.03.016

PPP with low-cost, single-frequency receivers has been receiving increasing interest in recent years because of its large amount of possible users. One crucial issue in single-frequency PPP is the mitigation of ionospheric delays which cannot be removed by combining observations on different frequencies. For this purpose, several approaches have been developed, such as, the approach using ionospheric model corrections with proper weight, the GRAPHIC (Group and Phase Ionosphere Calibration) approach, and the method to model ionospheric delays over a station with a low polynomial or stochastic process. From our investigation on the stochastic characteristics of the ionospheric delay over a station, it cannot be precisely represented by either a deterministic model in the form of a low-order polynomial or a stochastic process for each satellite, because of its strong irregular spatial and temporal variations. Therefore, a novel approach is developed accordingly in which the deterministic representation is further refined by a stochastic process for each satellite with an empirical model for its power density. Furthermore, ionospheric delay corrections from a constructed model using GNSS data are also included as pseudo-observations for a better solution. A large data set collected from about 200 IGS stations over one month in 2010 is processed with the new approach and several commonly adopted approaches for validation. The results show its significant improvements in terms of positioning accuracy and convergence time with a negligible extra processing time, which is also demonstrated by data collected with a low-cost, handheld, single-frequency receiver.