2026-09-23T08:53:35Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/127412 2026-02-03 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Soil moisture sensing is important to optimize water usage in agriculture and fire prevention. In agriculture, it enables smart irrigation systems to use water efficiently, reduce wastage, and enhance crop yields. For fire prevention, accurate soil moisture data improves estimates of fuel moisture levels, and helps to raise earlier wildfire warnings. Existing work on soil moisture measurement using RF signals can be categorized into contact-based and contactless methods. Contactless techniques, such as Ground Penetrating Radar (GPR), estimate soil moisture without direct soil contact but face challenges like high cost and limited signal penetration at greater heights. Contact-based methods, like burying a Wifi antenna or Lora antenna under soil, involve deploying sensors or reflectors underground, offering higher accuracy but often requiring complex setups, and high power consumption. This research introduces a hybrid system that integrates SFCW radar technology with wireless backscatter tags, offering a cost-effective, low-maintenance solution for accurate soil moisture sensing. Compared to previous RF-based approaches that buried an active and power-hungry transmitter under the soil, this approach buries a passive backscatter tag, which reflects a square wave from an active radar transmitter back to the receiver. The phase difference between the two antennas of the backscatter tag provides information about soil permittivity, which in turn indicates soil moisture. Controlled experiments demonstrate the the feasibility of inferring soil moisture from phase variations. 2024-12 Thesis https://hdl.handle.net/2142/127412 ©2024 Angquan Yu Soil Moisture Sensing Digital Signal Processing Stepped-frequency Continuous-wave (sfcw) Radar eng application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01 The student, Angquan Yu, accepted the attached license on 2024-12-10 at 17:16. The student, Angquan Yu, submitted this Thesis for approval on 2024-12-10 at 17:30. This Thesis was approved for publication on 2024-12-11 at 09:03. DSpace SAF Submission Ingestion Package generated from Vireo submission #21565 on 2025-03-28 at 14:45:02 Soltonaghai, Elahe Phase-based soil moisture sensing using radars and passive backscatter tags Yu, Angquan 2024-12-11 Electrical & Computer Eng Electrical & Computer Engr University of Illinois at Urbana-Champaign M.S. Thesis