Soil permittivity measurement using an inexpensive VNA-based TDR

Abstract

Time-domain reflectometry (TDR) is a widely used method for accurately measuring soil moisture in the field. This technique determines the relative permittivity of the soil by analyzing the change in the propagation speed of electromagnetic waves through a soil probe. However, conventional TDR equipment is expensive, often costing approximately one million yen, which limits its accessibility. Affordable vector network analyzers (VNAs) such as NanoVNA have emerged as potential alternatives for TDR measurements. Studies have demonstrated that VNAs can reproduce TDR waveforms with comparable accuracy to conventional equipment by converting frequency-domain reflectometry (FDR) data into time-domain waveforms. For example, NanoVNA was introduced recently to measure soil permittivity using three-wire probes accurately. However, this procedure often requires knowledge of digital signal processing; furthermore, the detailed steps for reproducing the results have not yet to be fully documented, creating challenges for widespread adoption. This study aimed to explain the theoretical principles and experimental procedures for reproducing TDR waveforms using NanoVNA. The discussion includes the basics of FDR-to-TDRconversion using the inverse fast Fourier transform (IFFT) and practical considerations, such as calibration, probe configuration, and data processing. In addition, examples of TDR waveformreproduction are reviewed, illustrating the accuracy of air and water permittivity measured. To promote broader accessibility, we provide open-source Python code that enables users to convert NanoVNA data into TDR waveforms. This article may support researchers and engineers in adopting NanoVNAbased TDR measurements as a low-cost yet reliable alternative to conventional TDR systems.