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Space-Borne GNSS-R Ionospheric Delay Error Elimination by Optimal Spatial Filtering.

Qiuyang Zhang1, Yang Liu1, Junming Xia2

  • 1School of Instrumentation and Opto-Electronic Engineering, Beihang University, Beijing 100191, China.

Sensors (Basel, Switzerland)
|September 30, 2020
PubMed
Summary

This study investigates ionospheric impacts on satellite-based Global Navigation Satellite System Reflectometry (GNSS-R) sea surface altimetry. Optimal spatial filtering methods were identified to minimize errors for improved accuracy.

Keywords:
ionospheric delayreflectometrysea surface altimetryspace-borne GNSS-Rspatial filtering

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Area of Science:

  • Earth and Space Science
  • Remote Sensing Technology
  • Geophysics

Background:

  • Satellite-based Global Navigation Satellite System Reflectometry (GNSS-R) is a novel remote sensing technique with significant potential for sea surface altimetry.
  • Ionospheric delays are a known source of error in GNSS-R measurements, potentially affecting altimetry accuracy.
  • Limited availability of satellite-borne GNSS-R orbit observations necessitates the use of simulated data for comprehensive studies.

Purpose of the Study:

  • To investigate the impact of ionospheric delays on space-borne GNSS-R sea surface altimetry.
  • To determine optimal spatial filtering parameters for mitigating ionospheric effects.
  • To enhance the accuracy and reliability of space-borne GNSS-R altimetry.

Main Methods:

  • Utilized simulated high-resolution space-borne GNSS-R orbital data for global analysis.
  • Analyzed the relationship between absolute bias and bilateral filtering points to find optimal values.
  • Employed statistical probability density and quantile analysis to validate the selected filtering parameters.

Main Results:

  • Identified optimal spatial filtering points that minimize absolute bias in GNSS-R sea surface altimetry.
  • Demonstrated the reliability of the chosen filtering values through statistical analysis.
  • Quantified the effectiveness of spatial filtering in reducing ionospheric delay impacts.

Conclusions:

  • The developed spatial filtering approach effectively mitigates ionospheric delays in space-borne GNSS-R altimetry.
  • The findings provide valuable guidance for future high-accuracy space-borne GNSS-R sea surface altimetry missions.
  • Optimized filtering techniques are crucial for advancing the application of GNSS-R technology in oceanographic studies.