To estimate the sea state bias（SSB） for radar altimeter, two nonparametric models, including a Nadaraya-Watson（NW） kernel estimator and a local linear regression（LLR） estimator, are studied based on the Jason-2 ...To estimate the sea state bias（SSB） for radar altimeter, two nonparametric models, including a Nadaraya-Watson（NW） kernel estimator and a local linear regression（LLR） estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained.展开更多
Most existing studies about passive radar systems are based on the already known illuminator of opportunity(IO)states.However,in practice,the receiver generally has little knowledge about the IO states.Little research...Most existing studies about passive radar systems are based on the already known illuminator of opportunity(IO)states.However,in practice,the receiver generally has little knowledge about the IO states.Little research has studied this problem.This paper analyzes the observability and estimability for passive radar systems with unknown IO states under three typical scenarios.Besides,the directions of high and low estimability with respect to various states are given.Moreover,two types of observations are taken into account.The effects of different observations on both observability and estimability are well analyzed.For the observability test,linear and nonlinear methods are considered,which proves that both tests are applicable to the system.Numerical simulations confirm the correctness of the theoretical analysis.展开更多
Using a convective scale WRF-GSI system and a reflectivity observation operator based on the double-moment microphysics(Thompson)scheme,simulated radar reflectivity data are produced and then directly assimilated with E...Using a convective scale WRF-GSI system and a reflectivity observation operator based on the double-moment microphysics(Thompson)scheme,simulated radar reflectivity data are produced and then directly assimilated with EnKF through Observing System Simulation Experi-ments(OSSEs)for the case of typhoon In-Fa(2021).We examined the ability of the EnKF to simultaneously estimate state variables and conducted sensitivity tests to evaluate the impact of updating different state variables.The results show that updating a full set of analysis variables can help obtain highly precise initialfields in the model and improve typhoon forecast skills.Excluding the horizontal wind update will affect the adjustment of the temperaturefield and the sea level pressurefield during the cyclic assimilation process.Updating the variables directly related to the reflectivity operator alone could adjust hydrometers well,but the positive impact arising from the assimilation quickly vanishes during the forecast.In addition,this study also includes a quantitative RMSE analysis for each variable during the assimilation cycle and compares the effect of each schemes on different variables.展开更多
A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a...A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.展开更多
A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed.Two experiments into the use of the radar system were carried out at two sites...A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed.Two experiments into the use of the radar system were carried out at two sites,respectively,for calibration process in Zhangzi Island of the Yellow Sea,and for validation in the Yellow Sea and South China Sea.Ocean wave parameters and sea surface current velocities were retrieved from the dual polarized radar image sequences based on an inverse method.The results obtained from dual-polarized radar data sets acquired in Zhangzi Island are compared with those from an ocean directional buoy.The results show that ocean wave parameters and sea surface current velocities retrieved from radar image sets are in a good agreement with those observed by the buoy.In particular,it has been found that the vertically-polarized radar is better than the horizontally-polarized radar in retrieving ocean wave parameters,especially in detecting the significant wave height below 1.0 m.展开更多
The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improv...The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improve the accuracy and increase the valid detection range of the wave height measurement, particularly by the smallaperture radar, it is turned to singular peaks which often exceed the power of other frequency components. The power of three kinds of singular peaks, i.e., those around ±1,±√2 and ±1√2 times the Bragg frequency, are retrieved from a one-month-long radar data set collected by an ocean state monitoring and analyzing radar,model S（OSMAR-S）, and in situ buoy records are used to make some comparisons. The power response to a wave height is found to be described with a new model quite well, by which obvious improvement on the wave height estimation is achieved. With the buoy measurements as reference, a correlation coefficient is increased to 0.90 and a root mean square error（RMSE） is decreased to 0.35 m at the range of 7.5 km compared with the results by the second-order method. The further analysis of the fitting performance across range suggests that the peak has the best fit and maintains a good performance as far as 40 km. The correlation coefficient is 0.78 and the RMSE is 0.62 m at 40 km. These results show the effectiveness of the new empirical method, which opens a new way for the wave height estimation with the HF radar.展开更多
Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where on...Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where one model is built on the data from only one radar altimeter.In this paper,taking account of the data from multiple radar altimeters available,we introduced a multi-task learning method,called trace-norm regularized multi-task learning(TNR-MTL),for SSB estimation.Corresponding to each individual task,TNR-MLT involves only three parameters.Hence,it is easy to implement.More importantly,the convergence of TNR-MLT is theoretically guaranteed.Compared with the commonly used STL models,TNR-MTL can effectively utilize the shared information between data from multiple altimeters.During the training of TNR-MTL,we used the JASON-2 and JASON-3 cycle data to solve two correlated SSB estimation tasks.Then the optimal model was selected to estimate SSB on the JASON-2 and the HY-270-71 cycle intersection data.For the JSAON-2 cycle intersection data,the corrected variance(M)has been reduced by 0.60 cm^2 compared to the geophysical data records(GDR);while for the HY-2 cycle intersection data,M has been reduced by 1.30 cm^2 compared to GDR.Therefore,TNR-MTL is proved to be effective for the SSB estimation tasks.展开更多
基金The National Key R&D Program of China under contract No.2016YFC1401004the National Natural Science Foundation of China under contract Nos 41406207,41176157 and 41406197
文摘To estimate the sea state bias（SSB） for radar altimeter, two nonparametric models, including a Nadaraya-Watson（NW） kernel estimator and a local linear regression（LLR） estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained.
基金This work was supported by the National Natural Science Foundation of China(61803379)the China Postdoctoral Science Foundation(2017M613370,2018T111129).
文摘Most existing studies about passive radar systems are based on the already known illuminator of opportunity(IO)states.However,in practice,the receiver generally has little knowledge about the IO states.Little research has studied this problem.This paper analyzes the observability and estimability for passive radar systems with unknown IO states under three typical scenarios.Besides,the directions of high and low estimability with respect to various states are given.Moreover,two types of observations are taken into account.The effects of different observations on both observability and estimability are well analyzed.For the observability test,linear and nonlinear methods are considered,which proves that both tests are applicable to the system.Numerical simulations confirm the correctness of the theoretical analysis.
基金the Program of Shanghai Academic/Technology Research Leader (21XD1404500)the National Key R&D Program of China (2018YFC1506404)the National Key R&D Program of China (2022YFC3080500).
文摘Using a convective scale WRF-GSI system and a reflectivity observation operator based on the double-moment microphysics(Thompson)scheme,simulated radar reflectivity data are produced and then directly assimilated with EnKF through Observing System Simulation Experi-ments(OSSEs)for the case of typhoon In-Fa(2021).We examined the ability of the EnKF to simultaneously estimate state variables and conducted sensitivity tests to evaluate the impact of updating different state variables.The results show that updating a full set of analysis variables can help obtain highly precise initialfields in the model and improve typhoon forecast skills.Excluding the horizontal wind update will affect the adjustment of the temperaturefield and the sea level pressurefield during the cyclic assimilation process.Updating the variables directly related to the reflectivity operator alone could adjust hydrometers well,but the positive impact arising from the assimilation quickly vanishes during the forecast.In addition,this study also includes a quantitative RMSE analysis for each variable during the assimilation cycle and compares the effect of each schemes on different variables.
文摘A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.
基金Supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Nos.KZCX1-YW-12-04,KZCX2-YW-201)the Instrument Developing Project of the Chinese Academy of Sciences (No.YZ200724)
文摘A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed.Two experiments into the use of the radar system were carried out at two sites,respectively,for calibration process in Zhangzi Island of the Yellow Sea,and for validation in the Yellow Sea and South China Sea.Ocean wave parameters and sea surface current velocities were retrieved from the dual polarized radar image sequences based on an inverse method.The results obtained from dual-polarized radar data sets acquired in Zhangzi Island are compared with those from an ocean directional buoy.The results show that ocean wave parameters and sea surface current velocities retrieved from radar image sets are in a good agreement with those observed by the buoy.In particular,it has been found that the vertically-polarized radar is better than the horizontally-polarized radar in retrieving ocean wave parameters,especially in detecting the significant wave height below 1.0 m.
基金The National Natural Science Foundation of China under contract No.61371198the National Special Program for Key Scientific Instrument and Equipment Development of China under contract No.2013YQ160793
文摘The popular methods to estimate wave height with high-frequency（HF） radar depend on the integration over the second-order spectral region and thus may come under from even not strong external interference. To improve the accuracy and increase the valid detection range of the wave height measurement, particularly by the smallaperture radar, it is turned to singular peaks which often exceed the power of other frequency components. The power of three kinds of singular peaks, i.e., those around ±1,±√2 and ±1√2 times the Bragg frequency, are retrieved from a one-month-long radar data set collected by an ocean state monitoring and analyzing radar,model S（OSMAR-S）, and in situ buoy records are used to make some comparisons. The power response to a wave height is found to be described with a new model quite well, by which obvious improvement on the wave height estimation is achieved. With the buoy measurements as reference, a correlation coefficient is increased to 0.90 and a root mean square error（RMSE） is decreased to 0.35 m at the range of 7.5 km compared with the results by the second-order method. The further analysis of the fitting performance across range suggests that the peak has the best fit and maintains a good performance as far as 40 km. The correlation coefficient is 0.78 and the RMSE is 0.62 m at 40 km. These results show the effectiveness of the new empirical method, which opens a new way for the wave height estimation with the HF radar.
基金This work was supported by the Major Project for New Generation of AI(No.2018AAA0100400)the National Natural Science Foundation of China(No.41706010)+1 种基金the Joint Fund of the Equipments Pre-Research and Ministry of Education of China(No.6141A020337)and the Fundamental Research Funds for the Central Universities of China.
文摘Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where one model is built on the data from only one radar altimeter.In this paper,taking account of the data from multiple radar altimeters available,we introduced a multi-task learning method,called trace-norm regularized multi-task learning(TNR-MTL),for SSB estimation.Corresponding to each individual task,TNR-MLT involves only three parameters.Hence,it is easy to implement.More importantly,the convergence of TNR-MLT is theoretically guaranteed.Compared with the commonly used STL models,TNR-MTL can effectively utilize the shared information between data from multiple altimeters.During the training of TNR-MTL,we used the JASON-2 and JASON-3 cycle data to solve two correlated SSB estimation tasks.Then the optimal model was selected to estimate SSB on the JASON-2 and the HY-270-71 cycle intersection data.For the JSAON-2 cycle intersection data,the corrected variance(M)has been reduced by 0.60 cm^2 compared to the geophysical data records(GDR);while for the HY-2 cycle intersection data,M has been reduced by 1.30 cm^2 compared to GDR.Therefore,TNR-MTL is proved to be effective for the SSB estimation tasks.
