Abstract's details
Using DORIS data in an OPerational Tool for Ionospheric MApping and Prediction
CoAuthors
Event: 2016 IDS Workshop
Session: Research activities and new applications
Presentation type: Type Oral
Contribution: not provided
Abstract:
At DGFI-TUM, a study has been conducted to combine different satellite observation techniques to develop an operational tool for ionospheric mapping, prediction and forecasting within the scope of an ongoing joint research project (OPTIMAP).
Terrestrial GNSS (e.g. GPS and GLONASS) observations provide a high-resolution coverage of the continental regions and have very high importance to study the variations of the ionospheric Vertical Total Electron Content (VTEC). However, large data gaps exist due to inhomogeneous global distribution of the GNSS observations sites, especially over the oceans. Thus, data acquired from additional satellite-based techniques such as GPS radio occultation measurements from the Formosat-3/COSMIC mission, altimetry and DORIS data, e.g. from the Jason-2 or Sentinel-3A mission can mitigate the data gap problem as well as contribute to a data densification on the terrestrial regions. In this context, carrier-phase data tracked by the on-board DORIS receivers are processed to provide total electron content observations for improving the spatio-temporal data coverage in VTEC modelling.
The spatial VTEC distribution in DGFI’s ionosphere modeling approach is represented by B-spline series expansions. The corresponding B-spline series coefficients together with additional technique-dependent unknowns such as GNSS Differential Code Biases, the DORIS phase ambiguity bias, and other inter-technique biases are estimated by a Kalman filter which allows sequential processing of the observations in a predictor-corrector mode.
Within this contribution, all the aforementioned observations are exploited in a sequential data preprocessing and filtering framework which is capable of assimilating observations from different space geodetic techniques to estimate ionospheric target parameters. In particular, the contribution of the DORIS data to the quality of the estimated VTEC products is investigated.
Terrestrial GNSS (e.g. GPS and GLONASS) observations provide a high-resolution coverage of the continental regions and have very high importance to study the variations of the ionospheric Vertical Total Electron Content (VTEC). However, large data gaps exist due to inhomogeneous global distribution of the GNSS observations sites, especially over the oceans. Thus, data acquired from additional satellite-based techniques such as GPS radio occultation measurements from the Formosat-3/COSMIC mission, altimetry and DORIS data, e.g. from the Jason-2 or Sentinel-3A mission can mitigate the data gap problem as well as contribute to a data densification on the terrestrial regions. In this context, carrier-phase data tracked by the on-board DORIS receivers are processed to provide total electron content observations for improving the spatio-temporal data coverage in VTEC modelling.
The spatial VTEC distribution in DGFI’s ionosphere modeling approach is represented by B-spline series expansions. The corresponding B-spline series coefficients together with additional technique-dependent unknowns such as GNSS Differential Code Biases, the DORIS phase ambiguity bias, and other inter-technique biases are estimated by a Kalman filter which allows sequential processing of the observations in a predictor-corrector mode.
Within this contribution, all the aforementioned observations are exploited in a sequential data preprocessing and filtering framework which is capable of assimilating observations from different space geodetic techniques to estimate ionospheric target parameters. In particular, the contribution of the DORIS data to the quality of the estimated VTEC products is investigated.