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 health
and ensuring optimal crop growth in agricultural environments. Accurate and large-scale mea-
surement of VWC, however, remains a significant challenge. Most commercially available
soil-moisture sensors are handheld, expensive, and impractical for monitoring fields that span
hundreds of acres. Furthermore, different crops require distinct moisture levels, and single-point
measurements 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-area
and 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 soil
permittivity.
This project aims to estimate soil permittivity using a Texas Instruments mmWave
radar by applying advanced digital signal processing (DSP) techniques to extract, analyze, and
interpret complex IQ data. Each radar chirp is processed using the ZoomFFT algorithm to
achieve high-resolution frequency estimation. The ZoomFFT enhances the system’s ability
to 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 are
then used to derive propagation delays, which are directly related to the effective dielectric
permittivity of the soil through established radar-based mathematical models.
Once the soil permittivity is estimated, empirical dielectric–moisture relationships
from the literature are applied to compute the corresponding VWC. This methodology provides
a non-contact, scalable, and efficient approach for soil moisture measurement. The overall
objective of the project is to demonstrate a remote-sensing framework that combines mmWave
radar and DSP techniques to deliver accurate, real-time, and wide-area VWC estimation for
precision agriculture applications.