Soil Moisture Estimation Based on GNSS-R Using L5 Signals From a Quasi-Zenith Satellite System

作者：Nazi Wang, Fan Gao, Yahui Kong, Tianhe Xu, Lili Jing, Lei Yang, Yunqiao He, Wentao Yang, Xinyue Meng, Baojiao Ning · 发表于：IEEE Geoscience and Remote Sensing Letters · 年份：2022 · DOI：10.1109/lgrs.2022.3176463 · 被引用次数：10 · 研究领域：Soil Moisture and Remote Sensing、Precipitation Measurement and Analysis、Synthetic Aperture Radar (SAR) Applications and Techniques

Global Navigation Satellite System Reflectometry (GNSS-R) is a passive technique for remote sensing of soil moisture, which has continuous all-day and all-weather applicability on different platforms. New GNSS signals with advanced modulation and higher power are expected to improve the performance of GNSS-R. In this study, we performed a ground-based dual-antenna GNSS-R experiment on farmland and collected 15-min raw intermediate frequency data with central frequency of 1175.42 MHz hourly over two different 24-h periods. The power ratio between the direct and reflected signals from QZSS satellites were computed using a self-developed software-defined receiver with 1-ms coherent integration and 200-ms incoherent adds. Then, soil moisture was resolved using a semiempirical model based on the power ratios. Solutions were evaluated using measurements obtained using a time-domain reflectometry probe. Results demonstrated that signal power-ratio-based QZSS signals can be used to retrieve soil moisture under bare soil conditions. Moreover, for signal power-ratio-based case, results from geostationary orbit (GEO) satellite signals (STD: 0.013 m3/m3 and 0.007 m3/m3) performed better than those from inclined geosynchronous orbit (IGSO) satellite signals (STD: 0.033–0.071 m3/m3).