Soil Moisture Content Inversion by Coupling AEA and ARMA

Abstract

This study aimed to explore the inversion method of soil moisture content by using numerical simulation and field detection. The researchers used the early signal amplitude envelope (AEA) method to directly invert soil moisture in the shallow part of the soil, which avoided the transmission error of the Topp formula. The Auto-Regressive Moving Average Model (ARMA) was used to calculate the power spectrum of radar signals, and the BP neural network was used to train the power spectrum of different Gaussian windows, so as to improve the inversion accuracy. According to the study, the average error of soil moisture content inverted by AEA method was 0.45% in the range of 0-0.41m, while the error of ARMA method in depth range of 0.1-1.0m was less than 1%. The results showed that the combination of the two methods can effectively invert the soil moisture content within the radar detection range.