| 利用窗口GPS多径干涉相位反演土壤湿度 |
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| 引用本文： | 敖敏思,朱建军,胡友健,叶险峰.利用窗口GPS多径干涉相位反演土壤湿度[J].武汉大学学报(信息科学版),2018,43(9):1328. |
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| 作者姓名： | 敖敏思 朱建军 胡友健 叶险峰 |
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| 作者单位： | 1.湖南省测绘科技研究所, 湖南 长沙, 410007 |
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| 基金项目： | 国家自然科学基金41371335湖南省重点研发计划2016SK2002湖南省科学技术厅战略性新兴产业项目2016GK4010湖南省科学技术厅中央引导地方专项2017KT5001长沙市科技计划KQ1701171 |
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| 摘 要： | 利用GPS信噪比（signal-to-noise ratio，SNR）观测值监测土壤湿度的精度直接受多径干涉相位与土壤湿度间的关系模型影响。传统方法基于线性模型，通过增加样本数量、排除特例提高普适性，但未合理考虑坡度、植被及天气等因素。基于上述因素短期变化可忽略的假设，引入时间窗口，采用自相关分析确定窗口长度，利用窗口内样本动态线性回归构建预测和插值模型反演土壤湿度。实验结果表明，引入窗口后，预测、插值误差分别下降17.4%和54.6%，相关系数上升16.2%和32.9%。插值模型利用了待估时刻之后的观测量，精度更高；预测模型精度略低，但更适于实时应用。同时，残差极大值与土壤湿度的上升之间显著相关。预测残差较土壤湿度具有极大值更小、时刻略微提前的时域特征。
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| 关 键 词： | 全球定位系统 信噪比 土壤湿度 多路径反射 干涉相位 |
| 收稿时间： | 2018-02-11 |
Retrieval Soil Moisture with GPS SNR Interferogram in Time Window |
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| Affiliation: | 1.Hunan Institute of Geomatics Science and Technology, Changsha 410007, China2.School of Geosciences and Info-Physics, Central South University, Changsha 410083, China3.Faculty of Information and Engineering, China University of Geosciences(Wuhan), Wuhan 430074, China4.College of Civil Engineering and Mechanics, Xiangtan University, Xiangtan, 411100, China |
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| Abstract: | The relationship model between the GPS multipath interferogram and soil moisture is a cri-tical factor for precise soil moisture monitoring. The traditional strategy is based on the linear model by collecting as many normal samples as possible during eliminating the outliers, however, it pays little attention to the factors which change slowly but affect the reflection environment such as slope, vegetation and weather. As the changes of these factors could be ignored in a short term, the time window is introduced. At first the window length is determined with correlation analysis, then the dynamic prediction and interpolation model could be realized by linear regression with samples within the window. The test results with real GPS, soil moisture and weather data show that, the prediction and interpolation error are reduced by 17.4% and 54.6%, and the correlation efficient are increased by 16.2% and 32.9% respectively. The interpolation is more accurate than prediction owing to the future samples, while the prediction model could be applied in real applications. The residual analysis show that the correlation between the epoch of maximal residue and soil moisture fluctuation exists. The maximal prediction residue is slightly weak and prior to the rises of soil moisture. |
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