Investigation of Multipath Signals from Navigation Satellites for the Retrieval of Surface Soil Moisture

Abstract

Soil moisture plays a crucial role in agriculture, weather forecasting, and climate modeling by enabling the proper management of water resources and optimizing crop yield. Accurately measuring soil moisture content is therefore essential. NavIC-IR (Interferometric Reflectometry), a satellite-based navigation system developed by the Indian Space Research Organization, offers a real-time solution to investigate soil moisture, providing more precise data and allowing for more accurate predictions of soil water content. In comparison to satellite missions like Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active and Passive mission (SMAP), which also provide soil moisture data, NavIC-IR has the advantage of higher accuracy and a shorter revisit time, facilitating more frequent and precise measurements. Although SMAP and SMOS missions offer data with spatial resolutions of 36 x 36 km and 25 x 25 km, respectively, and temporal resolutions of 2-3 days, their coarse resolution and extensive set-up requirements remain significant limitations. Advancing our knowledge of soil moisture through better technology can support the sustainability of ecosystems and enhance livelihoods that depend on them. The NavIC signal analysis for land applications focus on examining the behaviour difference between reflected and direct signals, similar to bistatic radar. The receiver receives multipath signal, i.e., both the reflected and direct signals at a specific distance from the reflecting surface,allowing for analysis of the reflecting surface characteristics. Utilizing three different NavIC-IR multipath parameters which are multipath amplitude, multipath phase, and multipath frequency, the technique has demonstrated its suitability for continuous soil moisture monitoring using a single ground-based antenna. This thesis comprehensively analyzes all three multipath observables for both bare and vegetated land, with high correlation observed for bare smooth soil surfaces, which decreases with surface roughness and vegetation