In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-f...In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillations introduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and life histories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme is proposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.For each scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.The results demonstrate the superiority of the multi-scale IAU scheme.展开更多
The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third...The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third dimensionality recognition.In this paper,combined with the actual triple star orbits,a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis(PCA)is presented.Firstly,interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain.Secondly,as a method with simple principle and fast calculation,the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics.Finally,the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA.The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49%and random noise introduced by the receiver.Meanwhile,due to the influence of orbit distribution of the actual triple star orbits,the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results.This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.展开更多
To deal with the non-Caussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduce...To deal with the non-Caussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduced into SAR tomography. With the estimated AR parameters of ARMA model of noise through Yule-Walker equation, the signal series of height is pre-filtered. Then, through ESPRIT, the spectrum is obtained and the aperture in height direction is synthesized. Finally, the SAR tomography imaging of scene is achieved. The results of processing on signal with non-Gaussian noise demonstrate the robustness of the proposed method. The tomography imaging of the scenes shows that the higher-order spectrum analysis is feasible in the application.展开更多
An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly hand...An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry.As for the issue,the analytical expression for the two Dimensional(2-D)signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study.The proposed simulator can accommodate the moving targets in the high squint geometry,whose processing steps of the simulation are given in detail and its computational complexity is analyzed.The simulation data for static and moving targets are processed and analyzed,and the results are given to validate the effectiveness of the proposed approach.展开更多
The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To ver...The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To verify this experimentally,a set of resonant magnetic perturbation(RMP) coils is required to excite coupled magnetic islands with different Δξ.The spectrum analysis shows that the current RMP coils on J-TEXT can only produce sufficient 2/1 and 3/1RMP fields with a limited phase difference of Δξ∈[-75°,75°].In order to broaden the adjustable range of Δξ,a set of coils on the high field side(HFS) is proposed to generate 2/1 and 3/1 RMP fields with Δξ=180°.As a result,RMPs with adjustable Δξ∈[-180°,180°] and sufficient amplitudes could be achieved by applying the HFS coils and the low field side(LFS)coils.This work provides a feasible solution for flexible adjustment of the phase difference between m and m+1 RMP,which might facilitate the study of major disruptions and their control.展开更多
One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is propo...One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is proposed. The 2-D nature of the algorithm provides it an advantage of circumventing the roundabout transforming procedures between two dimensional （2-D） image deta and one-dimensional （l-D） signal. Moreover the combination of the Newton （fixed-point algorithm） and natural gradient algorithms in this composite algorithm increases its efficiency and robustness. The convincing results of a successful example in functional magnetic resonance imaging （fMRI） show the potential application of composite 2-D ICA in the brain activity detection.展开更多
由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶...由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。展开更多
基金jointly sponsored by the Shenzhen Science and Technology Innovation Commission (Grant No. KCXFZ20201221173610028)the key program of the National Natural Science Foundation of China (Grant No. 42130605)
文摘In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillations introduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and life histories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme is proposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.For each scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.The results demonstrate the superiority of the multi-scale IAU scheme.
基金This work was supported by the General Design Department,China Academy of Space Technology(10377).
文摘The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third dimensionality recognition.In this paper,combined with the actual triple star orbits,a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis(PCA)is presented.Firstly,interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain.Secondly,as a method with simple principle and fast calculation,the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics.Finally,the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA.The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49%and random noise introduced by the receiver.Meanwhile,due to the influence of orbit distribution of the actual triple star orbits,the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results.This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.
基金supported partly by the New Century Excellent Talents in University(23901019)the Sichuan Provincial Youth Science and Technology Foundation(06ZQ026-006).
文摘To deal with the non-Caussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduced into SAR tomography. With the estimated AR parameters of ARMA model of noise through Yule-Walker equation, the signal series of height is pre-filtered. Then, through ESPRIT, the spectrum is obtained and the aperture in height direction is synthesized. Finally, the SAR tomography imaging of scene is achieved. The results of processing on signal with non-Gaussian noise demonstrate the robustness of the proposed method. The tomography imaging of the scenes shows that the higher-order spectrum analysis is feasible in the application.
文摘An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry.As for the issue,the analytical expression for the two Dimensional(2-D)signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study.The proposed simulator can accommodate the moving targets in the high squint geometry,whose processing steps of the simulation are given in detail and its computational complexity is analyzed.The simulation data for static and moving targets are processed and analyzed,and the results are given to validate the effectiveness of the proposed approach.
基金supported by the National Magnetic Confinement Fusion Energy R & D Program of China (Nos. 2018YFE0309102 and 2019YFE03010004)National Natural Science Foundation of China (Nos.12075096, 11905078,and 51821005)
文摘The phase difference Δξ between locked islands(2/1 and 3/1) has been found to influence the heat transport on the thermal quench during disruptions by numerical modeling [Hu Q et al 2019Nucl.Fusion 59,016005].To verify this experimentally,a set of resonant magnetic perturbation(RMP) coils is required to excite coupled magnetic islands with different Δξ.The spectrum analysis shows that the current RMP coils on J-TEXT can only produce sufficient 2/1 and 3/1RMP fields with a limited phase difference of Δξ∈[-75°,75°].In order to broaden the adjustable range of Δξ,a set of coils on the high field side(HFS) is proposed to generate 2/1 and 3/1 RMP fields with Δξ=180°.As a result,RMPs with adjustable Δξ∈[-180°,180°] and sufficient amplitudes could be achieved by applying the HFS coils and the low field side(LFS)coils.This work provides a feasible solution for flexible adjustment of the phase difference between m and m+1 RMP,which might facilitate the study of major disruptions and their control.
基金Supported by the 973 Project (No.2003CB716106), NSFC (No.90208003, 30200059), TRAPOYT, Doctor Training Fund of MOE, PRC, Key Research Project of Science and Technology of MOE, Fok Ying Tong Education Foundation (No.91041)
文摘One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is proposed. The 2-D nature of the algorithm provides it an advantage of circumventing the roundabout transforming procedures between two dimensional （2-D） image deta and one-dimensional （l-D） signal. Moreover the combination of the Newton （fixed-point algorithm） and natural gradient algorithms in this composite algorithm increases its efficiency and robustness. The convincing results of a successful example in functional magnetic resonance imaging （fMRI） show the potential application of composite 2-D ICA in the brain activity detection.
文摘由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。
