A GNSS-IR Multi-system Combination Soil Moisture Estimation Method Based on Track Clustering

Objectives Global navigation satellite system-interferometric reflectometry can be taken advantage of identifying soil moisture of land surface.

Methods Aiming at the problem of multi-GNSS combined soil moisture inversion, we use the phase extracted from the signal-to-noise ratio observation data of global positioning system (GPS), BeiDou satellite navigation system (BDS), GLONASS and Galileo system, and solve soil moisture inversion within consideration of satellite track clustering by using the empirical model. The estimation of multi-GNSS combination is obtained by weighted average method.

Results The inversion accuracy of BDS and Galileo is equivalent and superior to GPS and GLONASS. The root mean square error of the method in this paper is 0.041 4 cm³/cm³, which is about 16.3% and 5.2% lower than that of single navigation satellite system and the optimal frequency band respectively.

Conclusions The results indicate that the multi-GNSS reflection signal estimation method based on track clustering can effectively monitor changes in soil moisture.