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A Wavelet-Based Elevation Angle Selection Method for Soil Moisture Retrieval Using GNSS-IR.

Xilong Kou1, Yan Zhou1, Qian Chen1

  • 1College of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China.

Sensors (Basel, Switzerland)
|September 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive method for Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) soil moisture monitoring. The new approach improves accuracy by automatically selecting optimal satellite elevation angles, outperforming fixed intervals.

Keywords:
GNSS-IRelevation angle selectionsoil moisturewavelet

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Area of Science:

  • Remote Sensing
  • Geophysics
  • Signal Processing

Background:

  • Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) is a low-cost, high-precision technology for soil moisture monitoring.
  • Fixed elevation angle intervals in GNSS-IR struggle to adapt to varying satellite signal characteristics.
  • Accurate soil moisture retrieval relies on effective feature parameter extraction from satellite signals.

Purpose of the Study:

  • To develop an adaptive elevation angle interval selection method for GNSS-IR soil moisture retrieval.
  • To enhance the accuracy of soil moisture monitoring by optimizing satellite signal analysis.
  • To address the limitations of fixed elevation angle intervals in adapting to diverse satellite signals.

Main Methods:

  • Wavelet transform is employed to analyze the time-frequency characteristics of residual Signal-to-Noise Ratio (SNR) signals.
  • A ratio sequence of main frequency component strength to noise component strength is calculated.
  • A threshold is set to automatically determine the optimal retrieval elevation angle interval for each satellite.

Main Results:

  • The proposed adaptive method significantly improves soil moisture retrieval accuracy compared to traditional fixed intervals (5-20° and 5-30°).
  • Averaged phase feature parameters using algorithm-selected intervals yielded R² of 0.925 and RMSE of 0.55%, improving original results by 3.1% and 14.2%.
  • For low-quality reflection zones, R² increased by 13.2% (0.728 to 0.839) and RMSE decreased by 22.9% (1.045 to 0.806).

Conclusions:

  • The adaptive method effectively adjusts to signal quality attenuation across different reflection zones.
  • This strategy optimizes elevation angle interval selection for GNSS-IR soil moisture retrieval.
  • The developed technique enhances the reliability and precision of remote sensing-based soil moisture monitoring.