Lai et al. (2026) Improving the Accuracy of GNSS-IR-Based Soil Moisture Retrieval by Mitigating Phase Biases From Nonenvironmental Factors

Identification

• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Jianmin Lai, Changsheng Cai, Zhizhao Liu
• DOI: 10.1109/tgrs.2026.3665873

Research Groups

[Not provided in the given text]

Short Summary

The study focuses on enhancing the accuracy of soil moisture retrieval using GNSS-Interferometric Reflectometry (GNSS-IR) by developing and applying methods to mitigate phase biases caused by nonenvironmental factors.

Objective

• To improve the accuracy of soil moisture retrieval derived from GNSS-IR by identifying and mitigating phase biases attributed to nonenvironmental factors.

Study Configuration

• Spatial Scale: [Not provided in the given text]
• Temporal Scale: [Not provided in the given text]

Methodology and Data

• Models used: GNSS-IR processing algorithms for phase bias mitigation.
• Data sources: GNSS reflectometry signals.

Main Results

Expected: Demonstrated improvement in the accuracy of GNSS-IR-based soil moisture retrieval after applying the proposed phase bias mitigation techniques.

Contributions

Development of novel techniques or methodologies for mitigating nonenvironmental phase biases in GNSS-IR, leading to more robust and accurate soil moisture estimates.

Funding

[Not provided in the given text]

Citation

@article{Lai2026Improving,
  author = {Lai, Jianmin and Cai, Changsheng and Liu, Zhizhao},
  title = {Improving the Accuracy of GNSS-IR-Based Soil Moisture Retrieval by Mitigating Phase Biases From Nonenvironmental Factors},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2026},
  doi = {10.1109/tgrs.2026.3665873},
  url = {https://doi.org/10.1109/tgrs.2026.3665873}
}