The GNSS reflectometry technique provides geometric information on the environment surrounding the GNSS antenna including the vertical distance to a reflecting surface. We use sea-surface reflections of GPS signals, recorded as oscillations in signal-to-noise ratio (SNR), to estimate the GNSS to tide gauge (TG) levelling tie, and thus the ellipsoidal heights of the TG. We develop approaches to isolate SNR data dominated by sea-surface reflections and to remove SNR frequency changes caused by the dynamic sea surface. Comparison with in situ levelling at eight sites reveals mean differences at the centimetre level for satellites above 12º elevation, with four sites showing differences of 3 cm or smaller. These differences include errors in the in situ levelling, in the antenna calibration model and in the TG measurements, and so represent an upper bound on our technique’s error. Data sampling (1 or 30 s) does not significantly affect the results. We detect systematic errors at the decimetre level related to satellite elevations below 12◦ and to seasurface height and also differences between results from the L1 and L2 GPS signals larger than 15 cm at two sites. These systematic errors remain unexplained; differences between GPS signals are attributed to receiver-dependent differences in the SNR measurements, while the elevation-dependent error is attributed to unmodelled phase effects such as those caused by tropospheric refraction and sea-surface roughness. Using our approach, we identify a levelling offset of 1.5 cm related to a TG sensor change, illustrating our technique’s value for TG reference monitoring.

Item Type:	Refereed Article
Keywords:	GPS, sea level, height datums, reflectometry, GNSS, SNR, levelling, tide gauges, site co-location
Research Division:	Engineering
Research Group:	Geomatic engineering
Research Field:	Satellite-based positioning
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in the earth sciences
UTAS Author:	Santamaria-Gomez, A (Dr Alvaro Santamaria-Gomez)
UTAS Author:	Watson, C (Dr Christopher Watson)
UTAS Author:	King, M (Professor Matt King)
ID Code:	98105
Year Published:	2015
Funding Support:	Australian Research Council (FT110100207)
Web of Science® Times Cited:	51
Deposited By:	Geography and Environmental Studies
Deposited On:	2015-02-02
Last Modified:	2017-10-24
Downloads:	0