Soil moisture estimation based on triple-frequency multipath error

Abstract

ABSTRACT Soil moisture (SM) is a critical environmental factor. Therefore, it is of great significance to measure it dynamically and precisely. Studies have proved that Global Positioning System Reflectometry (GPS-R) based on signal-to-noise ratio can realize the monitoring of SM with high-precision, high spatiotemporal resolution, low cost, and under all weather conditions. The transmissions of GPS triple-frequency carrier phase (TRFCP) and triple-frequency pseudorange (TRFP) facilitate obtaining high-quality multipath errors in real-time. Accordingly, to enrich the data sources and methods for SM estimation based on GPS-R, two novel SM estimation methods – the TRFCP multipath error method (TRFCP method) and the TRFP multipath error method (TRFP method) – are proposed. The feasibility of the proposed methods was evaluated by the SM content (SMC) from the Plate Boundary Observatory (PBO) H2O project. The experimental results demonstrate that the phase delays estimated by the proposed methods both are strongly correlated with the PBO SMC, with Pearson correlation coefficients (R) of 0.95 and 0.84, respectively. Furthermore, both methods achieved high estimation accuracy for the SMC.