Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 19, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2022.3161409
Keywords
Global navigation satellite system; Signal to noise ratio; Receiving antennas; Global Positioning System; Instruments; Soil moisture; Attenuation; Amplitude ratio (AR); low-cost Global Navigation Satellite System (GNSS) instrument; refracted GNSS signal; signal-to-noise ratio (SNR); soil moisture (SM)
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Funding
- Fundamental Research Funds for the Central Universities [2042021kf0004]
- Innovative Research Group Project of National Natural Science Foundation of China [41721003, 42174022]
- Natural Science Foundation of Hubei Province of China [2019CFB427]
- Key Laboratory of Geospatial Environment and Geodesy, Ministry of Education, Wuhan University [19-02-06]
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The study proposes the use of GNSS technology for remotely sensing geophysical parameters, specifically soil moisture. By observing the attenuation of GNSS signal amplitude, the soil moisture can be accurately estimated. The results show that low-cost GNSS instruments can serve as cost-effective soil moisture sensors.
In the last 20 years, the reflected signal of Global Navigation Satellite System (GNSS) has been used for remotely sensing a series of geophysical parameters, resulting in two GNSS based remotely sensing techniques: GNSS reflectometry (GNSS-R) and GNSS interferometric reflectometry (GNSS-IR). In this letter, the refracted GNSS signal is first proposed to estimate near-surface soil moisture (SM). Amplitude of the refracted GNSS signal will attenuate when penetrated into soil due to refraction and propagation of the signal in the soil. Amplitude attenuation degree of the refracted signal is quantified as the amplitude ratio (AR) of the direct GNSS signal to the refracted signal. Two low-cost navigational GNSS chips and right-hand circularly polarized (RHCP) antennas are used to collect the refracted and direct GNSS signal in an experimental campaign, respectively. To simplify the modeling, the AR at elevation angle of 20 degrees is used to develop the model to describe the relationship between SM, AR, and soil temperature (ST) in the letter; and the AR and ST observation can be converted into SM accurately with a 2nd-order polynomial. The modeled SMs are strongly correlated with the sensor-based ones with correlation coefficient of 0.947 and root-mean-square error (RMSE) of 0.013 cm(3)/cm(3) (or, 1.3%) when SM is between 0.272 and 0.489 cm(3)/cm(3). The study also suggests that, based on the proposed method, the low-cost GNSS instrument can be treated as a new type of sensor monitoring SM in a cost-effective way.
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