Estimation of Soil Permittivity and Volumetric Water Content (VWC) Using mm-Wave Radar for Agricultural Applications

Volumetric water content (VWC) is a critical parameter for assessing soil healthand ensuring optimal crop growth in agricultural environments. Accurate and large-scale mea-surement of VWC, however, remains a significant challenge. Most commercially availablesoil-moisture sensors are handheld, expensive, and impractical for monitoring fields that spanhundreds of acres. Furthermore, different crops require distinct moisture levels, and single-pointmeasurements fail to capture the spatial variability present across large agricultural regions.Recent advancements in millimeter-wave (mmWave) radar technology offer a promis-ing alternative for remote, non-contact soil moisture estimation. mmWave radars are compact,low-cost, and capable of integration with unmanned aerial vehicles (UAVs), enabling wide-areaand continuous monitoring of soil conditions. Their high-frequency operation provides suffi-cient bandwidth to detect even small variations in signal propagation caused by changes in soilpermittivity.This project aims to estimate soil permittivity using a Texas Instruments mmWaveradar by applying advanced digital signal processing (DSP) techniques to extract, analyze, andinterpret complex IQ data. Each radar chirp is processed using the ZoomFFT algorithm toachieve high-resolution frequency estimation. The ZoomFFT enhances the system’s abilityto precisely identify the dominant spectral components associated with the reflected signals,enabling accurate calculation of the time-of-flight (ToF) for each chirp. The ToF values arethen used to derive propagation delays, which are directly related to the effective dielectricpermittivity of the soil through established radar-based mathematical models.Once the soil permittivity is estimated, empirical dielectric–moisture relationshipsfrom the literature are applied to compute the corresponding VWC. This methodology providesa non-contact, scalable, and efficient approach for soil moisture measurement. The overallobjective of the project is to demonstrate a remote-sensing framework that combines mmWaveradar and DSP techniques to deliver accurate, real-time, and wide-area VWC estimation forprecision agriculture applications.