| Citation: | SUN Bo, LIANG Yong, HAN Mutian, et al. A method for GNSS-IR soil moisture inversion based on GPS multi-satellite and triple-frequency data fusion[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(6): 1089-1096. doi: 10.13700/j.bh.1001-5965.2019.0396(in Chinese)
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Soil moisture monitoring is one of the key applications of Global Navigation Satellite System Interferometry and Reflectometry (GNSS-IR). Traditional GNSS-IR soil moisture inversion methods generally utilize only one frequency of single satellite, which lose the opportunities of taking full advantages of difference and complementarity of satellite signals with different orbits and frequencies. To solve this problem, this paper proposes a joint inversion method with weighting fusions of the L1, L2 and L5 frequency band data of GPS multi-satellite. In this method, the weighting factor is determined by an adaptive fusion algorithm based on the minimum variance. Field experiment is performed for verification. The results show that, compared with traditional Larson method on the test set, the correlation coefficient and the root-mean-square error of the inversion method proposed in this paper are 24.69% higher and 22.28% lower respectively, and meanwhile compared with the fusion method of the mean value method, the correlation coefficient and the root-mean-square error are 26.77% higher and 23.26% lower respectively. Experimental results prove that the proposed method can effectively improve the inversion accuracy.
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