Powell, C.E.; Ruf, C.S.; McKague, D.S.; Wang, T.; Russel, A. An Instrument Error Correlation Model for Global Navigation Satellite System Reflectometry. Remote Sens.2024, 16, 742.
Powell, C.E.; Ruf, C.S.; McKague, D.S.; Wang, T.; Russel, A. An Instrument Error Correlation Model for Global Navigation Satellite System Reflectometry. Remote Sens. 2024, 16, 742.
Powell, C.E.; Ruf, C.S.; McKague, D.S.; Wang, T.; Russel, A. An Instrument Error Correlation Model for Global Navigation Satellite System Reflectometry. Remote Sens.2024, 16, 742.
Powell, C.E.; Ruf, C.S.; McKague, D.S.; Wang, T.; Russel, A. An Instrument Error Correlation Model for Global Navigation Satellite System Reflectometry. Remote Sens. 2024, 16, 742.
Abstract
All sensing systems have some inherent error. Often, these errors are systematic, and observations taken within a similar region of space and time can have correlated error structure. However, the data from these systems are frequently assumed to have completely independent and uncorrelated error. This work introduces a correlated error model for GNSS-reflectometry (GNSS-R) using observations from NASA’s Cyclone Global Navigation Satellite System (CYGNSS). We validate our model against near-simultaneous observations between two CYGNSS satellites, and double difference our results with modeled observables to extract the correlated error structure due to the observing system itself. Our results are useful to catalogue for future GNSS-R missions and can be applied to construct an error covariance matrix for weather data assimilation.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
