A Real-Time On-Orbit Signal Tracking Algorithm for GNSS Surface Observations

This manuscript describes real-time on-orbit instrument compatible open loop signal tracking techniques for Global Navigation Satellite Systems (GNSS) reflection observations. All GNSS-reflection (GNSS-R) satellite instruments require algorithms which run in real-time on-board the satellite, that ar...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Remote sensing (Basel, Switzerland) Switzerland), 2019-08, Vol.11 (16), p.1858
1. Verfasser: Gleason, Scott
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This manuscript describes real-time on-orbit instrument compatible open loop signal tracking techniques for Global Navigation Satellite Systems (GNSS) reflection observations. All GNSS-reflection (GNSS-R) satellite instruments require algorithms which run in real-time on-board the satellite, that are capable of predicting the code phase time delay and Doppler frequency of surface reflected signals. The algorithms presented here are for open loop tracking techniques in reflected GNSS signals for the purposed of making surface remote sensing observations. Initially, the algorithms are demonstrated using high resolution sampled data from the NASA Cyclone GNSS (CYGNSS) mission over ocean and land surfaces. Subsequently. the algorithm performance over ocean regions is analyzed in detail using a larger data set. As part of the analysis, the algorithm is assessed for its speed of convergence, to demonstrate general compatibility with spacecraft instrument processing limitations. Results indicate that over ocean regions is it possible to robustly predict in real time the Doppler frequency and code phase time delay of multiple reflected signal to sufficient precision to make science observations of the scattering surface. These algorithms are intended to provide a baseline technique and variations from which the scientific community can design more specialized algorithms for individual applications.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs11161858