为研究GVR(G-band water Vapor Radiometer)机载微波辐射计自带反演算法在天津地区的适用性,将2016年北京探空资料分成春夏秋冬,对垂直累积液态水和垂直累积水汽的反演精度进行数值模拟检验。结果表明:垂直累积液态水反演精度随高度变...为研究GVR(G-band water Vapor Radiometer)机载微波辐射计自带反演算法在天津地区的适用性,将2016年北京探空资料分成春夏秋冬,对垂直累积液态水和垂直累积水汽的反演精度进行数值模拟检验。结果表明:垂直累积液态水反演精度随高度变化不明显,春夏秋冬4个季节反演结果相对偏差值范围分别为29%~78%、31%~71%、36%~67%、35%~79%,绝对偏差值范围分别为0.04~0.492 mm、0.075~0.294 mm、0.074~0.315mm、0.116~0.347mm;垂直累积水汽反演精度随高度降低(3000m以上降低更为明显),春、夏、秋、冬4个季节相对偏差3000m以下时分别为2.6%~20.8%、7.9%~19.1%、4.3%~16.5%、3.4%~14.2%,3000m以上时分别为6.4%~89.7%、12.5%~36.9%、13.2%~50%、11.8%~301%。与其他类型机载微波辐射计反演精度及GVR在北极地区地基观测反演精度相比,GVR自带反演算法在天津地区的垂直累积液态水和垂直累积水汽反演精度明显偏低。展开更多
Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption intro...Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption introduces much biases into the parameter estimates which greatly limits the accuracy of the vegetation height inversion.Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR.Nevertheless,the similar model parameter values in a multi-baseline model often lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm.To this end,we propose a new step-by-step inversion method applied to the multi-baseline observations.Firstly,an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data,and the regularized estimates of model parameters are obtained by regularization method.Then,the reliable estimates of GVR are determined by the MSE(mean square error)analysis of each regularized parameter estimation.Secondly,the estimated GVR is used to extracts the pure volume coherence,and then the vegetation height parameter is inverted from the pure volume coherence by least squares estimation.The experimental results show that the new method can improve the vegetation height inversion result effectively.The inversion accuracy is improved by 26%with respect to the three-stage method and the conventional solution of multi-baseline.All of these have demonstrated the feasibility and effectiveness of the new method.展开更多
机载微波辐射计(G-band water Vapor Radiometer,GVR)在使用过程中发现存在无线电频率干扰信号(Radio-Frequency Interference,RFI),为准确使用数据,需对干扰信号进行识别和订正。在分析多种RFI识别方法在GVR数据中的适用性基础上,根据...机载微波辐射计(G-band water Vapor Radiometer,GVR)在使用过程中发现存在无线电频率干扰信号(Radio-Frequency Interference,RFI),为准确使用数据,需对干扰信号进行识别和订正。在分析多种RFI识别方法在GVR数据中的适用性基础上,根据GVR探测及定标原理提出适用于GVR的RFI识别和订正方案。采用该方案对天津市2016年11月20日一次GVR亮温数据进行识别和订正,结果表明,该方法能较好的识别出各通道亮温数据中的RFI信号;RFI存在于多个通道中,时空分布无规律,具有随机性,为干扰源确定带来较大困难;RFI在亮温数据中除少数以孤立点形式存在,多数为连续干扰点,连续干扰点越多,订正效果越差,当连续干扰点较多时建议剔除该部分数据。RFI订正前后的反演结果对比分析表明,多数情况下,RFI的存在使得垂直累积水汽和垂直累积液态水含量值被高估,少数值被低估,单个通道做订正对反演结果的影响不同。展开更多
基金National Natural Science Foundation of China(No.42104025)China Postdoctoral Science Foundation(No.2021M702509)+3 种基金Natural Resources Sciences and Technology Project of Hunan Province(No.2022-07)Surveying and Mapping Basic Research Foundation of Key Laboratory of Geospace Environment and Geodesy,Ministry of Education(No.20-01-04)Natural Science Foundation of Hunan Province(No.2024JJ5144)Open Fund of Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway(Changsha University of Science&Technology,No.kfj190805).
文摘Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption introduces much biases into the parameter estimates which greatly limits the accuracy of the vegetation height inversion.Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR.Nevertheless,the similar model parameter values in a multi-baseline model often lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm.To this end,we propose a new step-by-step inversion method applied to the multi-baseline observations.Firstly,an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data,and the regularized estimates of model parameters are obtained by regularization method.Then,the reliable estimates of GVR are determined by the MSE(mean square error)analysis of each regularized parameter estimation.Secondly,the estimated GVR is used to extracts the pure volume coherence,and then the vegetation height parameter is inverted from the pure volume coherence by least squares estimation.The experimental results show that the new method can improve the vegetation height inversion result effectively.The inversion accuracy is improved by 26%with respect to the three-stage method and the conventional solution of multi-baseline.All of these have demonstrated the feasibility and effectiveness of the new method.
文摘机载微波辐射计(G-band water Vapor Radiometer,GVR)在使用过程中发现存在无线电频率干扰信号(Radio-Frequency Interference,RFI),为准确使用数据,需对干扰信号进行识别和订正。在分析多种RFI识别方法在GVR数据中的适用性基础上,根据GVR探测及定标原理提出适用于GVR的RFI识别和订正方案。采用该方案对天津市2016年11月20日一次GVR亮温数据进行识别和订正,结果表明,该方法能较好的识别出各通道亮温数据中的RFI信号;RFI存在于多个通道中,时空分布无规律,具有随机性,为干扰源确定带来较大困难;RFI在亮温数据中除少数以孤立点形式存在,多数为连续干扰点,连续干扰点越多,订正效果越差,当连续干扰点较多时建议剔除该部分数据。RFI订正前后的反演结果对比分析表明,多数情况下,RFI的存在使得垂直累积水汽和垂直累积液态水含量值被高估,少数值被低估,单个通道做订正对反演结果的影响不同。
