针对IGS RTS(real time service)实时数据流产品难以避免的数据中断现象,开展了RTS数据中断修复方法研究,提出"插值修复"方法。在对RTS数据中断的区间分布进行统计分析的基础上,选取15min为可修复的最大数据中断区间;采用常...针对IGS RTS(real time service)实时数据流产品难以避免的数据中断现象,开展了RTS数据中断修复方法研究,提出"插值修复"方法。在对RTS数据中断的区间分布进行统计分析的基础上,选取15min为可修复的最大数据中断区间;采用常用的拉格朗日插值方法进行RTS轨道数据中断修复,对不同阶数的插值修复效果进行比较;提出新的基于RTS改正的精密卫星钟差计算方法,采用拉格朗日插值、三次样条插值、线性插值和线性拟合等方法进行RTS钟差数据中断修复和结果对比;最后利用IGS跟踪站观测数据和修复后的RTS产品,进行静态模拟动态的准实时PPP实验,对"插值修复"方法的效果和PPP定位精度进行验证。展开更多
传统多相并联的15 k W无线电能传输系统进行电能计量数据远传时,未考虑谐波背景下电流能量不均衡问题,导致系统的运行稳定性较低。因此,研究谐波背景下,非线性供电系统的电能计量数据远传技术,将80C196KC当成非线性供电系统的核心,系统...传统多相并联的15 k W无线电能传输系统进行电能计量数据远传时,未考虑谐波背景下电流能量不均衡问题,导致系统的运行稳定性较低。因此,研究谐波背景下,非线性供电系统的电能计量数据远传技术,将80C196KC当成非线性供电系统的核心,系统硬件由数据远传模块、键盘模块以及LCD液晶显示模块等构成,其中数据远传模块通过隔离电路在全部周期共同远传脉冲的掌控下,将电压和电流信号远传到单片机中进行分析,采用锁相环电路对信号进行全部周期共同远传处理;系统软件采用模块化设计,在监控循环模块、采集模块以及其他功能模块中,设计定时中断服务程序与数据接收程序,实现谐波背景下非线性供电系统的电能计量数据有效远传。实验结果表明,所设计系统进行电能计量数据远传时远传误差率增长不高于0. 26%,远传速度增长率最大值为98%,具有较高的传速度增长快、远传效率和鲁棒性,且系统实现复杂度和系统成本较低。展开更多
On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random in...On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.展开更多
文摘针对IGS RTS(real time service)实时数据流产品难以避免的数据中断现象,开展了RTS数据中断修复方法研究,提出"插值修复"方法。在对RTS数据中断的区间分布进行统计分析的基础上,选取15min为可修复的最大数据中断区间;采用常用的拉格朗日插值方法进行RTS轨道数据中断修复,对不同阶数的插值修复效果进行比较;提出新的基于RTS改正的精密卫星钟差计算方法,采用拉格朗日插值、三次样条插值、线性插值和线性拟合等方法进行RTS钟差数据中断修复和结果对比;最后利用IGS跟踪站观测数据和修复后的RTS产品,进行静态模拟动态的准实时PPP实验,对"插值修复"方法的效果和PPP定位精度进行验证。
文摘传统多相并联的15 k W无线电能传输系统进行电能计量数据远传时,未考虑谐波背景下电流能量不均衡问题,导致系统的运行稳定性较低。因此,研究谐波背景下,非线性供电系统的电能计量数据远传技术,将80C196KC当成非线性供电系统的核心,系统硬件由数据远传模块、键盘模块以及LCD液晶显示模块等构成,其中数据远传模块通过隔离电路在全部周期共同远传脉冲的掌控下,将电压和电流信号远传到单片机中进行分析,采用锁相环电路对信号进行全部周期共同远传处理;系统软件采用模块化设计,在监控循环模块、采集模块以及其他功能模块中,设计定时中断服务程序与数据接收程序,实现谐波背景下非线性供电系统的电能计量数据有效远传。实验结果表明,所设计系统进行电能计量数据远传时远传误差率增长不高于0. 26%,远传速度增长率最大值为98%,具有较高的传速度增长快、远传效率和鲁棒性,且系统实现复杂度和系统成本较低。
基金Project supported by the State Key Program of the National Natural Science of China (Grant No. 60835004)the Natural Science Foundation of Jiangsu Province of China (Grant No. BK2009727)+1 种基金the Natural Science Foundation of Higher Education Institutions of Jiangsu Province of China (Grant No. 10KJB510004)the National Natural Science Foundation of China (Grant No. 61075028)
文摘On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.
