| Citation: | JING Lili, YANG Lei, HAN Moutian, et al. Soil moisture inversion method based on GNSS-IR dual frequency data fusion[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(6): 1248-1255. doi: 10.13700/j.bh.1001-5965.2018.0555(in Chinese)
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At present, the study of soil moisture inversion in the field of global navigation satellite signal-interferometer and reflectometry (GNSS-IR) is only for single frequency deployment. In the paper, we propose a method that uses the entropy method to fuse two frequency to improve the accuracy of soil moisture inversion. First, the spectrum analysis method is used to analyze the oscillation frequency of the signal-to-noise ratio (SNR) sequence of each frequency point, and calculate the corresponding equivalent antenna height. The different frequency phase of SNR sequence can be solved by least square method. Then, the phase observation of two frequencies is fused by the entropy method. Finally, an empirical model was established by using the fusion results and the measured soil moisture to achieve soil moisture inversion. The method was verified by global positioning system (GPS) SNR ratio data obtained in frequency L1 and L2 by ground-based observation experiments. The results show that the average standard deviation of the L1 and L2 inversion results after dual frequency fusion is 0.6%, which is 64.73% higher than the L1 frequency inversion results and 32.12% higher than the L2 frequency inversion results. And the RMSE is 0.37%, 72.8% lower than L1 frequency and 73.4% lower than L2 frequency.
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