【摘要】 土壤水是作物生长发育直接水源，土壤含水量是监测作物旱情的最重要的指标。目前土壤含水量检测算法无法满足大规模的监测需要，存在精度较低，易受天气、地表状况等因素影响的问题。微波测量方法能解决上述问题，但是当前该方法采用时域脉冲，具有噪声大等问题。基于去噪声能力强的矢量网络分析仪采用频域扫描方法，使用菲涅尔反射系数进行反演，建立土壤含水量和介电常数关系模型。反演结果表明，不同含水量的土壤介电常数存在明显差别，得到的含水量的精确度能够满足设计要求。更多还原

【Abstract】 Soil water is the direct source of water for crop growth and development, and soil water content is the most important indicator for monitoring crop drought. The current soil water content detection algorithm cannot meet the needs of large-scale monitoring, which has low accuracy, and is easily affected by factors such as weather and surface conditions. The microwave measurement method can solve the above problems, but the current method adopts the time-domain pulse, which has problems such as large noise. The vector network analyzer with strong denoising ability adopts the frequency domain scanning method, the Fresnel reflection coefficient is used to invert, and establishes the relationship model between soil water content and dielectric constant. The inversion results show that there are obvious differences in the dielectric constant of soils with different water contents, and the accuracy of the obtained water contents can meet the design requirements更多还原