The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the ...The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.展开更多
针对常规地震易损性分析方法的不足,引入基于对数变换核密度估计与Copula函数相结合的半参数(transformed kernel density estimation and Copula,TKC)构件易损性分析方法及可有效考虑构件响应相关性的基于R-vine Copula函数的系统易损...针对常规地震易损性分析方法的不足,引入基于对数变换核密度估计与Copula函数相结合的半参数(transformed kernel density estimation and Copula,TKC)构件易损性分析方法及可有效考虑构件响应相关性的基于R-vine Copula函数的系统易损性分析方法,系统开展“构件-系统”两层次易损性分析。通过与一阶界限法对比,验证了所采用方法的合理性和准确性。为揭示典型铁路减隔震桥梁系统的损伤特性及抗震性能,以某7×32 m双线铁路减隔震简支梁桥为工程背景,建立轨道-桥梁系统精细化非线性动力分析模型,实现构件及系统层面的易损性分析。构建了适用于铁路减隔震桥梁的三水准抗震性能评估体系,对桥梁抗震性能进行全面评估。研究表明:减隔震支座在地震作用下最易发生损伤,其次为轨道、桥墩;支座体系主导系统的轻微、中等损伤,轨道体系主导系统的严重损伤和完全破坏。因此,实际工程中应重点加强支座体系的抗震设计,同时采取必要措施提高轨道体系的抗震能力,确保桥梁系统整体性能达到预期标准。展开更多
基金supported by the National Natural Science Foundation of China under Grant No.12072090.
文摘The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.
文摘针对常规地震易损性分析方法的不足,引入基于对数变换核密度估计与Copula函数相结合的半参数(transformed kernel density estimation and Copula,TKC)构件易损性分析方法及可有效考虑构件响应相关性的基于R-vine Copula函数的系统易损性分析方法,系统开展“构件-系统”两层次易损性分析。通过与一阶界限法对比,验证了所采用方法的合理性和准确性。为揭示典型铁路减隔震桥梁系统的损伤特性及抗震性能,以某7×32 m双线铁路减隔震简支梁桥为工程背景,建立轨道-桥梁系统精细化非线性动力分析模型,实现构件及系统层面的易损性分析。构建了适用于铁路减隔震桥梁的三水准抗震性能评估体系,对桥梁抗震性能进行全面评估。研究表明:减隔震支座在地震作用下最易发生损伤,其次为轨道、桥墩;支座体系主导系统的轻微、中等损伤,轨道体系主导系统的严重损伤和完全破坏。因此,实际工程中应重点加强支座体系的抗震设计,同时采取必要措施提高轨道体系的抗震能力,确保桥梁系统整体性能达到预期标准。
