Title
Circular Regression Applied to GNSS-R Phase Altimetry.
Abstract
This article is dedicated to the design of a linear-circular regression technique and to its application to ground-based GNSS-Reflectometry (GNSS-R) altimetry. The altimetric estimation is based on the observation of the phase delay between a GNSS signal sensed directly and after a reflection off of the Earth's surface. This delay evolves linearly with the sine of the emitting satellite elevation, with a slope proportional to the height between the reflecting surface and the receiving antenna. However, GNSS-R phase delay observations are angular and affected by a noise assumed to follow the von Mises distribution. In order to estimate the phase delay slope, a linear-circular regression estimator is thus defined in the maximum likelihood sense. The proposed estimator is able to fuse phase observations obtained from several satellite signals. Moreover, unlike the usual unwrapping approach, the proposed estimator allows the sea-surface height to be estimated from datasets with large data gaps. The proposed regression technique and altimeter performances are studied theoretically, with further assessment on both synthetic and real data.
Year
DOI
Venue
2017
10.3390/rs9070651
REMOTE SENSING
Keywords
Field
DocType
GNSS-reflectometry,altimetry,circular statistics,GNSS signal processing
Altimeter,GNSS reflectometry,Satellite,Remote sensing,von Mises distribution,Group delay and phase delay,GNSS applications,Elevation,Geology,Geodesy,Estimator
Journal
Volume
Issue
ISSN
9
7
2072-4292
Citations 
PageRank 
References 
1
0.37
11
Authors
5
Name
Order
Citations
PageRank
Jean-Christophe Kucwaj161.96
Serge Reboul2257.02
Georges Stienne333.17
Jean-Bernard Choquel4445.67
Mohammed Benjelloun516324.87