For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the ...For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error(RMSE)between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression(MLR),artificial neural networks(ANN) and one-dimensional variational(1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.展开更多
Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filterin...Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filtering method based on fractional Fourier transform to suppress random noise in 3D seismic data. First, the seismic data is transformed to the time-frequency plane via the fractional Fourier transform. Second, based on the Eigenimage filtering method and Cadzow filtering method, the mixed high-dimensional Hankel matrix is built; then, SVD is performed. Finally, random noise is eliminated effectively by reducing the rank of the matrix. The theoretical model and real applications of the mixed filtering method in a region of Sichuan show that our method can not only suppress noise effectively but also preserve the frequency and phase of effective signals quite well and significantly improve the signal-to-noise ratio of 3D post-stack seismic data.展开更多
Herein,a three-dimensional(3D)inversion method in the frequency domain based on a time–frequency transformation was developed to improve the efficiency of the 3D inversion of transient electromagnetic(TEM)data.The Fo...Herein,a three-dimensional(3D)inversion method in the frequency domain based on a time–frequency transformation was developed to improve the efficiency of the 3D inversion of transient electromagnetic(TEM)data.The Fourier transform related to the electromagnetic response in the frequency and time domains becomes a sine or cosine transform under the excitation of downward-step current.We established a transformation matrix based on the digital fi ltering calculation for the sine transform,and then the frequency domain projection of the TEM data was determined from the linear transformation system using the smoothing constrained least squares inversion method,in which only the imaginary part was used to maintain the TEM data transformation equivalence in the bidirectional projection.Thus,the time-domain TEM inversion problem was indirectly and effectively solved in the frequency domain.In the 3D inversion of the transformed frequency-domain data,the limited-memory Broyden–Fletcher–Goldfarb–Shannoquasi–Newton(L-BFGS)method was used and modifi ed with a restart strategy to adjust the regularization parameter when the algorithm tended to a local minimum.Synthetic data tests showed that our domain transformation method can stably project the TEM data into the frequency domain with very high accuracy;furthe rmore,the 3D inversion of the transformed frequency-domain data is stable,can be used to recover the real resistivity model with an acceptable effi ciency.展开更多
基金Key Fostering Project of National Space Science Center,Chinese Academy of Sciences(Y62112f37s)National 863 Project of China(2015AA8126027)
文摘For Microwave Humidity and Temperature sounder(MWHTS) measurements over the ocean, a cloud filtering method is presented to filter out cloud-and precipitation-affected observations by analyzing the sensitivity of the simulated brightness temperatures of MWHTS to cloud liquid water, and using the root mean square error(RMSE)between observation and simulation in clear sky as a reference standard. The atmospheric temperature and humidity profiles are retrieved using MWHTS measurements with and without filtering by multiple linear regression(MLR),artificial neural networks(ANN) and one-dimensional variational(1DVAR) retrieval methods, respectively, and the effects of the filtering method on the retrieval accuracies are analyzed. The numerical results show that the filtering method can improve the retrieval accuracies of the MLR and the 1DVAR retrieval methods, but have little influence on that of the ANN. In addition, the dependencies of the retrieval methods upon the testing samples of brightness temperature are studied, and the results show that the 1DVAR retrieval method has great stability due to that the testing samples have great impact on the retrieval accuracies of the MLR and the ANN, but have little impact on that of the 1DVAR.
基金sponsored by the major science and technology special topic of CNPC(No.2013E-38-08)
文摘Conventional frequency domain method used in random noise attenuation singular value decomposition （SVD） filtering processing causes bending event damage. To mitigate this problem, we present a mixed Cadzow filtering method based on fractional Fourier transform to suppress random noise in 3D seismic data. First, the seismic data is transformed to the time-frequency plane via the fractional Fourier transform. Second, based on the Eigenimage filtering method and Cadzow filtering method, the mixed high-dimensional Hankel matrix is built; then, SVD is performed. Finally, random noise is eliminated effectively by reducing the rank of the matrix. The theoretical model and real applications of the mixed filtering method in a region of Sichuan show that our method can not only suppress noise effectively but also preserve the frequency and phase of effective signals quite well and significantly improve the signal-to-noise ratio of 3D post-stack seismic data.
基金the National Key Research and Development Program of China(No.2016YFC060110403).
文摘Herein,a three-dimensional(3D)inversion method in the frequency domain based on a time–frequency transformation was developed to improve the efficiency of the 3D inversion of transient electromagnetic(TEM)data.The Fourier transform related to the electromagnetic response in the frequency and time domains becomes a sine or cosine transform under the excitation of downward-step current.We established a transformation matrix based on the digital fi ltering calculation for the sine transform,and then the frequency domain projection of the TEM data was determined from the linear transformation system using the smoothing constrained least squares inversion method,in which only the imaginary part was used to maintain the TEM data transformation equivalence in the bidirectional projection.Thus,the time-domain TEM inversion problem was indirectly and effectively solved in the frequency domain.In the 3D inversion of the transformed frequency-domain data,the limited-memory Broyden–Fletcher–Goldfarb–Shannoquasi–Newton(L-BFGS)method was used and modifi ed with a restart strategy to adjust the regularization parameter when the algorithm tended to a local minimum.Synthetic data tests showed that our domain transformation method can stably project the TEM data into the frequency domain with very high accuracy;furthe rmore,the 3D inversion of the transformed frequency-domain data is stable,can be used to recover the real resistivity model with an acceptable effi ciency.
