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《第九届中国卫星导航学术年会论文集——S01 卫星导航应用技术》2018年
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Research on Multi-satellites Fusion Inversion Model of Soil Moisture Based on Sliding Window

Yueji Liang  Chao Ren  Yibang Huang  
【摘要】:Global Positioning System Interferometric Reflectometry(GPS-IR) is a new remote sensing technique,and it can be used to estimate near surface soil moisture from signal-to-noise ratio data.Considering the advantages of multi-satellite convergence and the time and space scale of soil moisture,a multi-satellites fusion inversion model of soil moisture based on sliding window is proposed.Firstly,the direct and reflection signals of GPS satellites are separated by a low order polynomial fitting,and then the sinusoidal fitting model of reflection signals is established,the relative phase of the SNR interferogram is obtained.Finally,a sliding window is established to select the relative phases of the satellites effectively,and the best input variables of the inversion model are determined.Then,the soil moisture is retrieved by least square support vector machine.Based on the monitoring data provided by US Plate Boundary Observations Project,the feasibility and effectiveness of using single and different GPS satellites to sliding estimate soil moisture are compared and analyzed.The experimental results show that sliding window can effectively select GPS satellites and determine the best input variables for the model.The model fully takes the advantage of non-linear weight determination.The sliding type can achieve a longer time inversion.To a certain extent,this model improves the phenomenon that the inversion process is prone to jump when using single satellite inversion.Based on the inversion of more than four satellites,RMSE and MAE is less than 0.07 and 0.06,respectively,and R2 is increased by at least 21.9% compared with inversion result of a single satellite.Therefore,the inversion of soil moisture can be treated as nonlinear event,and multi-satellites fusion inversion is feasible and effective.
【分类号】:S127;S152.7

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