Optimizing Waveform Maximum Determination for Specular Point Tracking in Airborne GNSS-R.

Area of Science:

• Geosciences
• Remote Sensing
• Signal Processing

Background:

• Airborne GNSS-R is vital for studying Earth's surface interactions.
• Signal interpretation is challenging due to aircraft geometry, especially over forests or with direct signal interference.
• Existing methods often overestimate reflectivity or result in unusable data.

Purpose of the Study:

• To develop and present optimized processing techniques for airborne GNSS-R data.
• To improve the accuracy and robustness of GNSS-R measurements under non-optimal conditions.
• To enhance the overall usability of airborne GNSS-R datasets.

Main Methods:

• Analysis of data from the GLORI instrument during a 2015 airborne campaign in France.
• Development of techniques for improved determination of reflected waveform peaks in the delay dimension.
• Algorithm focused on accurate localization of waveform maxima, even with low reflectivity or direct signal contamination.

Main Results:

• The developed technique allows for correction and extraction of real reflectivity values near the specular point.
• Application to the complete dataset demonstrated improved accuracy and sensitivity.
• Data usability was enhanced by 30% through the refined processing algorithm.

Conclusions:

• Optimized airborne GNSS-R data processing techniques significantly improve measurement quality.
• The new methods successfully address challenges posed by complex environments and signal interference.
• This advancement increases the reliability and utility of airborne GNSS-R data for scientific research.