Process variations can reduce the accuracy in estimation of interconnect performance. This work presents a process variation based stochastic model and proposes an effective analytical method to estimate interconnect ...Process variations can reduce the accuracy in estimation of interconnect performance. This work presents a process variation based stochastic model and proposes an effective analytical method to estimate interconnect delay. The technique decouples the stochastic interconnect segments by an improved decoupling method. Combined with a polynomial chaos expression （PCE）, this paper applies the stochastic Galerkin method （SGM） to analyze the system response. A finite representation of interconnect delay is then obtained with the complex approximation method and the bisection method. Results from the analysis match well with those from SPICE. Moreover, the method shows good computational efficiency, as the running time is much less than the SPICE simulation＇s.展开更多
Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analys...Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analyses to systematically examine the spatiotemporal patterns of runoff and its climatic driving mechanisms across Tajikistan,providing a scientific basis for sustainable water resource utilization and management in the study area.Results indicated that during 2000–2024,the annual runoff in Tajikistan exhibited statistically non-significant long-term trend(P=0.76),while displaying pronounced seasonal variability and strong spatial heterogeneity.Spring and summer average runoff primarily exhibited slight declining tendencies,while winter average runoff exhibited pronounced reduction in localized regions,such as the Syr Darya Basin,the Vakhsh River Basin,and the lower reaches of the Zeravshan River Basin.Precipitation emerged as the dominant positive driver of runoff,exhibiting moderate to strong positive correlations across over 78.00%of the country,whereas potential evapotranspiration consistently functioned as a negative driver.Rising temperatures exerted a dual competitive effect on runoff:in high-elevation,glacier-covered regions,rising temperatures temporarily increased runoff by accelerating glacier melt;however,at the national scale,the negative impact of rising temperature on runoff has played a slightly dominant role to a certain extent by enhancing evapotranspiration.Collectively,these results indicated that the present stability of runoff in Tajikistan is strongly dependent on the short-term compensatory effects of glacier melt and the risk of future runoff decline is likely to intensify as glacier reserves continue to diminish.This study provides a critical scientific evidence to inform sustainable water resource management in Tajikistan and underscores the need for glacier conservation and integrated water resource management strategies.展开更多
This paper analyzes the dynamic characteristics of the variations of the beach volumes for three level zonesof the Yanjing Beach in the Shuidong Bay of the western Guangdong Province by using the methods of dynamic sy...This paper analyzes the dynamic characteristics of the variations of the beach volumes for three level zonesof the Yanjing Beach in the Shuidong Bay of the western Guangdong Province by using the methods of dynamic systemanalysis and the multi-dimensional spectral estimation. The results show that the variations of the beach volume arecharaCterized by the multiband oscillations with a dominant semimonth period. Upwards the low tide level, the beachtends to be stable. The estimates of the partial coherences and the partial phases indicate that the variations of thebeach volumes are mainly the results of the direct actions of the waves which are influenced by the tidal level changesand driven by the wind stress. The simulation results of the beach volume series for different beach heart zones bythreshold mixed regressive models indicate that the influence of the tide on the variations of the beach volumes is weakened and the direct actions of the wave energy and the wind stress are apparently enhanced with the increase of thebeach height.(This project was supported by the National Natural Science Foundation of China.)展开更多
Formation flying Low Earth Orbiters(LEOs)are important for implementing new and advanced concepts in Earth observation missions.Precise Baseline Determination(PBD)is a prerequisite for LEOs to complete specified missi...Formation flying Low Earth Orbiters(LEOs)are important for implementing new and advanced concepts in Earth observation missions.Precise Baseline Determination(PBD)is a prerequisite for LEOs to complete specified mission targets.PBD is usually performed based on space-borne GNSS data,the relative corrections of phase center and code residual variations play crucial roles in achieving the best relative orbit accuracy.Herein,the influences of antenna Relative Phase Centre Variations(RPCVs)and Single-Difference(SD)Melbourne-Wu¨bbena(MW)Combination Residuals Variations(SD MWVs)on PBD are studied.The methods were tested using flight data from Gravity Recovery And Climate Experiment(GRACE)and GRACE Follow-On(GRACE-FO).Results showed that the maximum values for RPCVs and SD MWVs were 14 mm and 0.32 cycles,respectively.Then,the RPCVs correction significantly enhanced the baseline accuracy;the K-Band Ranging(KBR)measurement consistency improved by 30.1%and 37.5%for GRACE and GRACE-FO,respectively.The application of SD MWVs further improved the accuracy and reliability of PBD results.For GRACE,the ambiguities fixing success rate increased from 85.1%to 97.9%and a baseline consistency of 0.57 mm was achieved for the KBR measurements.It was found that the correction of both RPCVs and SD MWVs reduced the carrier phase observation minus computation residuals from double-difference ionosphere-free combination.In addition,in-flight data processing demonstrated that RPCVs and SD MWVs estimations for the current period could be used for the previous and subsequent periods.展开更多
The measurement of atmospheric water vapor （WV） content and variability is important for meteorological and climatological research. A technique for the remote sensing of atmospheric WV content using ground-based Gl...The measurement of atmospheric water vapor （WV） content and variability is important for meteorological and climatological research. A technique for the remote sensing of atmospheric WV content using ground-based Global Positioning System （GPS） has become available, which can routinely achieve accuracies for integrated WV content of 1-2 kg/m2. Some experimental work has shown that the accuracy of WV measurements from a moving platform is comparable to that of （static） land-based receivers. Extending this technique into the marine environment on a moving platform would be greatly beneficial for many aspects of meteorological research, such as the calibration of satellite data, investigation of the air-sea interface, as well as forecasting and climatological studies. In this study, kinematic precise point positioning has been developed to investigate WV in the Arctic Ocean （80°-87°N） and annual variations are obtained for 2008 and 2012 that are identical to those related to the enhanced greenhouse effect.展开更多
In-flight phase center systematic errors of global positioning system（GPS） receiver antenna are the main restriction for improving the precision of precise orbit determination using dual-frequency GPS.Residual appro...In-flight phase center systematic errors of global positioning system（GPS） receiver antenna are the main restriction for improving the precision of precise orbit determination using dual-frequency GPS.Residual approach is one of the valid methods for in-flight calibration of GPS receiver antenna phase center variations（PCVs） from ground calibration.In this paper,followed by the correction model of spaceborne GPS receiver antenna phase center,ionosphere-free PCVs can be directly estimated by ionosphere-free carrier phase post-fit residuals of reduced dynamic orbit determination.By the data processing of gravity recovery and climate experiment（GRACE） satellites,the following conclusions are drawn.Firstly,the distributions of ionosphere-free carrier phase post-fit residuals from different periods have the similar systematic characteristics.Secondly,simulations show that the influence of phase residual estimations for ionosphere-free PCVs on orbit determination can reach the centimeter level.Finally,it is shown by in-flight data processing that phase residual estimations of current period could not only be used for the calibration for GPS receiver antenna phase center of foretime and current period,but also be used for the forecast of ionosphere-free PCVs in future period,and the accuracy of orbit determination can be well improved.展开更多
Consider a first-order autoregressive processes , where the innovations are nonnegative random variables with regular variation at both the right endpoint infinity and the unknown left endpoint θ. We propose estimate...Consider a first-order autoregressive processes , where the innovations are nonnegative random variables with regular variation at both the right endpoint infinity and the unknown left endpoint θ. We propose estimates for the autocorrelation parameter f and the unknown location parameter θ by taking the ratio of two sample values chosen with respect to an extreme value criteria for f and by taking the minimum of over the observed series, where represents our estimate for f. The joint limit distribution of the proposed estimators is derived using point process techniques. A simulation study is provided to examine the small sample size behavior of these estimates.展开更多
We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without ...We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without further restrictions. The novelty of this article is to expand the current research practice by developing a hierarchical Bayesian approach with the assumption that the odds of recapture bears a constant relationship to the odds of initial capture. A real-data example of deer mice population is given to illustrate the proposed method. Three simulation studies are developed to inspect the performance of the proposed Bayesian estimates. Compared with the maximum likelihood estimates discussed in Chao et al. (2000), the hierarchical Bayesian estimate provides reasonably better population estimation with less mean square error;moreover, it is sturdy to underline relationship between the initial and re-capture probabilities. The sensitivity study shows that the proposed Bayesian approach is robust to the choice of hyper-parameters. The third simulation study reveals that both relative bias and relative RMSE approach zero as population size increases. A R-package is developed and used in both data example and simulation.展开更多
The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equa...The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.展开更多
Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yie...Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.展开更多
Due to the pulse interference, measurement outliers and artificial modeling errors, the multivariate skew t noise widely exists in the real environment. However, to date, little attention has been paid to the state es...Due to the pulse interference, measurement outliers and artificial modeling errors, the multivariate skew t noise widely exists in the real environment. However, to date, little attention has been paid to the state estimation for systems in which the process noise and the measurement noise are both modeled as the heavy-tailed and skew non-Gaussian noise. In this paper, the multivariate skew t distribution is utilized to model the heavy-tailed and skew non-Gaussian noise. Then a probabilistic graphical form of the multivariate skew t distribution is given and proved. Based on the probabilistic graphical form, a hierarchical Gaussian state space model for stochastic uncertain systems is proposed, which transforms the estimation problem for systems with the heavy-tailed and skew non-Gaussian noises into the one with a hierarchical Gaussian state space model. Next, given the designed Gaussian state space model, the robust Bayesian filter and smoother based on the variational Bayesian inference are proposed to approximately estimate the system state and the unknown noise parameters. Furthermore, the complexity analysis together with the controllability and observability for stochastic uncertain systems with multivariate skew t noises is given. Finally,the simulation results of the target tracking scenario verify the validity of the proposed algorithms.展开更多
With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between ...With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between the base reflectivity Z observed by radar and real time precipitation I by rain gauge. Then, the Doppler radar observations of base reflectivity for typhoons Haitang and Matsa in Wenzhou are employed to establish various Z-I relationships, which are subsequently used to estimate hourly precipitation of the two typhoons. Such estimations are calibrated by variational techniques. The results show that there exist significant differences in the Z-I relationships for the typhoons, leading to different typhoon precipitation efficiencies. The typhoon precipitation estimated by applying radar base reflectivity is capable of exhibiting clearly the spiral rain belts and mesoscale cells, and well matches the observed rainfall. Error statistical analyses indicate that the estimated typhoon precipitation is better with variational calibration than the one without. The variational calibration technique is able to maintain the characteristics of the distribution of radar-estimated typhoon precipitation, and to significantly reduce the error of the estimated precipitation in comparison with the observed rainfall.展开更多
It is critical to have precise data about Lithium-ion batteries,such as the State-of-Charge(SoC),to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles.Numerous s...It is critical to have precise data about Lithium-ion batteries,such as the State-of-Charge(SoC),to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles.Numerous strategies for estimating battery SoC,such as by including the coulomb counting and Kalman filter,have been established.As a result of the differences in parameter values between each cell,when these methods are applied to highcapacity battery packs,it has difficulties sustaining the prediction accuracy of overall cells.As a result of aging,the variation in the parameters of each cell is higher as more time is spent in operation.It is suggested in this study to establish an SoC estimate model for a Lithium-ion battery by employing an enhanced Deep Neural Network(DNN)approach.This is because the proposed DNN has a substantial hidden layer,which can accurately predict the SoC of an unknown driving cycle during training,making it ideal for SoC estimation.To evaluate the nonlinearities between voltage and current at various SoCs and temperatures,the proposed DNN is applied.Using current and voltage data measured at various temperatures throughout discharge/charge cycles is necessary for training and testing purposes.When the method has been thoroughly trained with the data collected,it is used for additional cells cycle tests to predict their SoC.The simulation has been conducted for two different Li-ion battery datasets.According to the experimental data,the suggested DNN-based SoC estimate approach produces a low mean absolute error and root-mean-square-error values,say less than 5%errors.展开更多
Quantum power system state estimation(QPSSE)offers an inspiring direction for tackling the challenge of state estimation through quantum computing.Nevertheless,the current bottlenecks originate from the scarcity of pr...Quantum power system state estimation(QPSSE)offers an inspiring direction for tackling the challenge of state estimation through quantum computing.Nevertheless,the current bottlenecks originate from the scarcity of practical and scalable QPSSE methodologies in the noisy intermediate-scale quantum(NISQ)era.This paper devises a NISQ−QPSSE algorithm that facilitates state estimation on real NISQ devices.Our new contributions include:(1)A variational quantum circuit(VQC)-based QPSSE formulation that empowers QPSSE analysis utilizing shallow-depth quantum circuits;(2)A variational quantum linear solver(VQLS)-based QPSSE solver integrating QPSSE iterations with VQC optimization;(3)An advanced NISQ-compatible QPSSE methodology for tackling the measurement and coefficient matrix issues on real quantum computers;(4)A noise-resilient method to alleviate the detrimental effects of noise disturbances.The encouraging test results on the simulator and real-scale systems affirm the precision,universal-ity,and scalability of our QPSSE algorithm and demonstrate the vast potential of QPSSE in the thriving NISQ era.展开更多
文摘Process variations can reduce the accuracy in estimation of interconnect performance. This work presents a process variation based stochastic model and proposes an effective analytical method to estimate interconnect delay. The technique decouples the stochastic interconnect segments by an improved decoupling method. Combined with a polynomial chaos expression （PCE）, this paper applies the stochastic Galerkin method （SGM） to analyze the system response. A finite representation of interconnect delay is then obtained with the complex approximation method and the bisection method. Results from the analysis match well with those from SPICE. Moreover, the method shows good computational efficiency, as the running time is much less than the SPICE simulation＇s.
基金funded by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0720203)the National Key Research and Development Program of China(2023YFF0805603).
文摘Based on monthly runoff and climate datasets spanning 2000–2024,this study employed the Theil–Sen’s slope estimation,Mann–Kendall(M–K)trend test,as well as Pearson correlation and Spearman rank correlation analyses to systematically examine the spatiotemporal patterns of runoff and its climatic driving mechanisms across Tajikistan,providing a scientific basis for sustainable water resource utilization and management in the study area.Results indicated that during 2000–2024,the annual runoff in Tajikistan exhibited statistically non-significant long-term trend(P=0.76),while displaying pronounced seasonal variability and strong spatial heterogeneity.Spring and summer average runoff primarily exhibited slight declining tendencies,while winter average runoff exhibited pronounced reduction in localized regions,such as the Syr Darya Basin,the Vakhsh River Basin,and the lower reaches of the Zeravshan River Basin.Precipitation emerged as the dominant positive driver of runoff,exhibiting moderate to strong positive correlations across over 78.00%of the country,whereas potential evapotranspiration consistently functioned as a negative driver.Rising temperatures exerted a dual competitive effect on runoff:in high-elevation,glacier-covered regions,rising temperatures temporarily increased runoff by accelerating glacier melt;however,at the national scale,the negative impact of rising temperature on runoff has played a slightly dominant role to a certain extent by enhancing evapotranspiration.Collectively,these results indicated that the present stability of runoff in Tajikistan is strongly dependent on the short-term compensatory effects of glacier melt and the risk of future runoff decline is likely to intensify as glacier reserves continue to diminish.This study provides a critical scientific evidence to inform sustainable water resource management in Tajikistan and underscores the need for glacier conservation and integrated water resource management strategies.
文摘This paper analyzes the dynamic characteristics of the variations of the beach volumes for three level zonesof the Yanjing Beach in the Shuidong Bay of the western Guangdong Province by using the methods of dynamic systemanalysis and the multi-dimensional spectral estimation. The results show that the variations of the beach volume arecharaCterized by the multiband oscillations with a dominant semimonth period. Upwards the low tide level, the beachtends to be stable. The estimates of the partial coherences and the partial phases indicate that the variations of thebeach volumes are mainly the results of the direct actions of the waves which are influenced by the tidal level changesand driven by the wind stress. The simulation results of the beach volume series for different beach heart zones bythreshold mixed regressive models indicate that the influence of the tide on the variations of the beach volumes is weakened and the direct actions of the wave energy and the wind stress are apparently enhanced with the increase of thebeach height.(This project was supported by the National Natural Science Foundation of China.)
基金supported by the National Natural Science Foundation of China(Nos.41874028,61803018)。
文摘Formation flying Low Earth Orbiters(LEOs)are important for implementing new and advanced concepts in Earth observation missions.Precise Baseline Determination(PBD)is a prerequisite for LEOs to complete specified mission targets.PBD is usually performed based on space-borne GNSS data,the relative corrections of phase center and code residual variations play crucial roles in achieving the best relative orbit accuracy.Herein,the influences of antenna Relative Phase Centre Variations(RPCVs)and Single-Difference(SD)Melbourne-Wu¨bbena(MW)Combination Residuals Variations(SD MWVs)on PBD are studied.The methods were tested using flight data from Gravity Recovery And Climate Experiment(GRACE)and GRACE Follow-On(GRACE-FO).Results showed that the maximum values for RPCVs and SD MWVs were 14 mm and 0.32 cycles,respectively.Then,the RPCVs correction significantly enhanced the baseline accuracy;the K-Band Ranging(KBR)measurement consistency improved by 30.1%and 37.5%for GRACE and GRACE-FO,respectively.The application of SD MWVs further improved the accuracy and reliability of PBD results.For GRACE,the ambiguities fixing success rate increased from 85.1%to 97.9%and a baseline consistency of 0.57 mm was achieved for the KBR measurements.It was found that the correction of both RPCVs and SD MWVs reduced the carrier phase observation minus computation residuals from double-difference ionosphere-free combination.In addition,in-flight data processing demonstrated that RPCVs and SD MWVs estimations for the current period could be used for the previous and subsequent periods.
基金Chinese Polar Environment Comprehensive Investigation and Assessment Programmes under contract Nos CHINARE2013-03-03 and CHINARE 2013-04-03the National Oceanic Commonweal Research Project under contract No.201105001the National Natural Science Foundation of China under contract No.41374043
文摘The measurement of atmospheric water vapor （WV） content and variability is important for meteorological and climatological research. A technique for the remote sensing of atmospheric WV content using ground-based Global Positioning System （GPS） has become available, which can routinely achieve accuracies for integrated WV content of 1-2 kg/m2. Some experimental work has shown that the accuracy of WV measurements from a moving platform is comparable to that of （static） land-based receivers. Extending this technique into the marine environment on a moving platform would be greatly beneficial for many aspects of meteorological research, such as the calibration of satellite data, investigation of the air-sea interface, as well as forecasting and climatological studies. In this study, kinematic precise point positioning has been developed to investigate WV in the Arctic Ocean （80°-87°N） and annual variations are obtained for 2008 and 2012 that are identical to those related to the enhanced greenhouse effect.
基金National Natural Science Foundation of China(61002033,60902089)Open Research Fund of State Key Laboratory of Astronautic Dynamics of China (2011ADL-DW0103)
文摘In-flight phase center systematic errors of global positioning system（GPS） receiver antenna are the main restriction for improving the precision of precise orbit determination using dual-frequency GPS.Residual approach is one of the valid methods for in-flight calibration of GPS receiver antenna phase center variations（PCVs） from ground calibration.In this paper,followed by the correction model of spaceborne GPS receiver antenna phase center,ionosphere-free PCVs can be directly estimated by ionosphere-free carrier phase post-fit residuals of reduced dynamic orbit determination.By the data processing of gravity recovery and climate experiment（GRACE） satellites,the following conclusions are drawn.Firstly,the distributions of ionosphere-free carrier phase post-fit residuals from different periods have the similar systematic characteristics.Secondly,simulations show that the influence of phase residual estimations for ionosphere-free PCVs on orbit determination can reach the centimeter level.Finally,it is shown by in-flight data processing that phase residual estimations of current period could not only be used for the calibration for GPS receiver antenna phase center of foretime and current period,but also be used for the forecast of ionosphere-free PCVs in future period,and the accuracy of orbit determination can be well improved.
文摘Consider a first-order autoregressive processes , where the innovations are nonnegative random variables with regular variation at both the right endpoint infinity and the unknown left endpoint θ. We propose estimates for the autocorrelation parameter f and the unknown location parameter θ by taking the ratio of two sample values chosen with respect to an extreme value criteria for f and by taking the minimum of over the observed series, where represents our estimate for f. The joint limit distribution of the proposed estimators is derived using point process techniques. A simulation study is provided to examine the small sample size behavior of these estimates.
文摘We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without further restrictions. The novelty of this article is to expand the current research practice by developing a hierarchical Bayesian approach with the assumption that the odds of recapture bears a constant relationship to the odds of initial capture. A real-data example of deer mice population is given to illustrate the proposed method. Three simulation studies are developed to inspect the performance of the proposed Bayesian estimates. Compared with the maximum likelihood estimates discussed in Chao et al. (2000), the hierarchical Bayesian estimate provides reasonably better population estimation with less mean square error;moreover, it is sturdy to underline relationship between the initial and re-capture probabilities. The sensitivity study shows that the proposed Bayesian approach is robust to the choice of hyper-parameters. The third simulation study reveals that both relative bias and relative RMSE approach zero as population size increases. A R-package is developed and used in both data example and simulation.
基金Supported by the Navy Equipment Department Foundation under Grant No. 2009(189)
文摘The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions and constraint equations in the variational method are constructed by analyzing input and output equations of the system. The problem of parameter estimation was transformed into a problem of least squares estimation. The parameter estimation equation was analyzed in order to get an optimized estimation of parameters based on the Lagrange multiplication operator. Simulation results showed that this method is better than the traditional least squares estimation, producing a higher precision when identifying parameters. It has very important practical value in areas of application such as system identification and parameter estimation.
基金supported by the National Natural Science Foundation of China(No.52272390)the Natural Science Foundation of Heilongjiang Province of China(No.YQ2022A009)the Shanghai Sailing Program,China(No.20YF1417300).
文摘Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.
基金supported by the National Natural Science Foundation of China (Nos.61603040 and 61433003)Yunnan Applied Basic Research Project of China (No.201701CF00037)Yunnan Provincial Science and Technology Department Key Research Program (Engineering), China (No.2018BA070)。
文摘Due to the pulse interference, measurement outliers and artificial modeling errors, the multivariate skew t noise widely exists in the real environment. However, to date, little attention has been paid to the state estimation for systems in which the process noise and the measurement noise are both modeled as the heavy-tailed and skew non-Gaussian noise. In this paper, the multivariate skew t distribution is utilized to model the heavy-tailed and skew non-Gaussian noise. Then a probabilistic graphical form of the multivariate skew t distribution is given and proved. Based on the probabilistic graphical form, a hierarchical Gaussian state space model for stochastic uncertain systems is proposed, which transforms the estimation problem for systems with the heavy-tailed and skew non-Gaussian noises into the one with a hierarchical Gaussian state space model. Next, given the designed Gaussian state space model, the robust Bayesian filter and smoother based on the variational Bayesian inference are proposed to approximately estimate the system state and the unknown noise parameters. Furthermore, the complexity analysis together with the controllability and observability for stochastic uncertain systems with multivariate skew t noises is given. Finally,the simulation results of the target tracking scenario verify the validity of the proposed algorithms.
基金Key Project of Social Development in Zhejiang Province (2006C13025, 2007C13G1610002)
文摘With the pros and cons of the traditional optimization and probability pairing methods thoroughly considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between the base reflectivity Z observed by radar and real time precipitation I by rain gauge. Then, the Doppler radar observations of base reflectivity for typhoons Haitang and Matsa in Wenzhou are employed to establish various Z-I relationships, which are subsequently used to estimate hourly precipitation of the two typhoons. Such estimations are calibrated by variational techniques. The results show that there exist significant differences in the Z-I relationships for the typhoons, leading to different typhoon precipitation efficiencies. The typhoon precipitation estimated by applying radar base reflectivity is capable of exhibiting clearly the spiral rain belts and mesoscale cells, and well matches the observed rainfall. Error statistical analyses indicate that the estimated typhoon precipitation is better with variational calibration than the one without. The variational calibration technique is able to maintain the characteristics of the distribution of radar-estimated typhoon precipitation, and to significantly reduce the error of the estimated precipitation in comparison with the observed rainfall.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University(KKU)for funding this research project Number(R.G.P.2/133/43).
文摘It is critical to have precise data about Lithium-ion batteries,such as the State-of-Charge(SoC),to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles.Numerous strategies for estimating battery SoC,such as by including the coulomb counting and Kalman filter,have been established.As a result of the differences in parameter values between each cell,when these methods are applied to highcapacity battery packs,it has difficulties sustaining the prediction accuracy of overall cells.As a result of aging,the variation in the parameters of each cell is higher as more time is spent in operation.It is suggested in this study to establish an SoC estimate model for a Lithium-ion battery by employing an enhanced Deep Neural Network(DNN)approach.This is because the proposed DNN has a substantial hidden layer,which can accurately predict the SoC of an unknown driving cycle during training,making it ideal for SoC estimation.To evaluate the nonlinearities between voltage and current at various SoCs and temperatures,the proposed DNN is applied.Using current and voltage data measured at various temperatures throughout discharge/charge cycles is necessary for training and testing purposes.When the method has been thoroughly trained with the data collected,it is used for additional cells cycle tests to predict their SoC.The simulation has been conducted for two different Li-ion battery datasets.According to the experimental data,the suggested DNN-based SoC estimate approach produces a low mean absolute error and root-mean-square-error values,say less than 5%errors.
基金supported in part by the National Science Foundation under Grant No.ITE-2134840.This work relates to Department of Navy award N00014-23-1-2124 issued by the Office of Naval Research.The United States Government has a royalty-free license throughout the world in all copyrightable material contained herein.
文摘Quantum power system state estimation(QPSSE)offers an inspiring direction for tackling the challenge of state estimation through quantum computing.Nevertheless,the current bottlenecks originate from the scarcity of practical and scalable QPSSE methodologies in the noisy intermediate-scale quantum(NISQ)era.This paper devises a NISQ−QPSSE algorithm that facilitates state estimation on real NISQ devices.Our new contributions include:(1)A variational quantum circuit(VQC)-based QPSSE formulation that empowers QPSSE analysis utilizing shallow-depth quantum circuits;(2)A variational quantum linear solver(VQLS)-based QPSSE solver integrating QPSSE iterations with VQC optimization;(3)An advanced NISQ-compatible QPSSE methodology for tackling the measurement and coefficient matrix issues on real quantum computers;(4)A noise-resilient method to alleviate the detrimental effects of noise disturbances.The encouraging test results on the simulator and real-scale systems affirm the precision,universal-ity,and scalability of our QPSSE algorithm and demonstrate the vast potential of QPSSE in the thriving NISQ era.
