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kalman滤波器增益
相关语句
  kalman filter gain
     NEW ALGORITHMS OF STEAD STATE KALMAN FILTER GAIN
     稳态Kalman滤波器增益新算法
短句来源
     Using the modern time series analysis method, based on the controlled autoregressive moving average(CARMA) innovation model, two new algorithms of steady state Kalman filter gain for stochastic control systems are presented, where the solution of the Riccati equation is avoided.
     应用现代时间序列分析方法,基于受控的自回归滑动平均(CARMA)新息模型,提出了随机控制系统稳态Kalman滤波器增益的两种新算法,避免了求解Riccati方程.
短句来源
     A New Algorithm of Steady-state Kalman Filter Gain
     稳态Kalman滤波器增益的一种新算法
短句来源
     Using the modern time series analysis, based on the ARMA innovation model. this paper presents a new algorithm of steady-state Kalman filter gain.
     用现代时间序列分析方法,基于ARMA新息模型,提出了稳态Kalman滤波器增益阵的一种新算法。
短句来源
     By using the modern time series analysis method and based on the ARMA innovation model,two new algorithms of steady state Kalman filter gain are presented,and their equivalence is proved. The self tuning Kalman filters can be implemented by using a recursive identifier of parameters for the ARMA innovation model,in conjunction with the new algorithms. A simulation example shows usefulness of the proposed algorithms.
     应用现代时间序列分析方法,基于ARMA新息模型,提出了稳态Kalman滤波器增益的两种简单的新算法,并证明了它们的等价性.应用ARMA新息模型参数的递推辨识器伴随新算法,可实现自校正Kalman滤波器.仿真例子说明了其有效性.
短句来源
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  “kalman滤波器增益”译为未确定词的双语例句
     A new adaptive Kalman filter is presented for the single output system with unknown noise statistics. By a time series analysis, a new and simpler estimation algorithm for the gain of the steady-state optimal Kalman filter is given.
     对于带未知噪声统计的单输出系统,本文提出了一种新的自适应Kalman滤波器,应用现代时间序列分析方法,基于ARMA新息模型的滑动平均(MA)参数的在线辨识,提出了稳态最优Kalman滤波器增益估计的一种新算法,比Mehra的算法简单。
短句来源
     And Lyapunov equations are presented for computing the filtering error variance and covariance matrices among sensors, which can be solved by iteration. The exponential convergence of the iterative solution is proved.
     基于ARMA新息模型计算稳态Kalman滤波器增益,提出了计算传感器之间的滤波误差方差阵和协方差阵的Lyapunov方程,它可用迭代法求解,并证明了迭代解的指数收敛性.
短句来源
     The concept of steady-state Kalman filter is presented,and the steady-state value of the gain matrix is used to calculate the Kalman filter.
     提出了稳态Kalm an滤波器的概念,并用Kalm an滤波器增益阵的稳态值计算Kal-m an滤波器。
短句来源
  相似匹配句对
     NEW ALGORITHMS OF STEAD STATE KALMAN FILTER GAIN
     稳态Kalman滤波器增益新算法
短句来源
     A New Algorithm of Steady-state Kalman Filter Gain
     稳态Kalman滤波器增益的一种新算法
短句来源
     The anti-jamming algorithm of Kalman filter
     Kalman滤波器的抗干扰算法
短句来源
     Running Status Recognize Of Kalman Filter In Real Time
     Kalman滤波器工作状态的实时辨识
     SYSTEM GAIN OF MULTI-CHANNEL WIENER FILTER
     多通路维纳滤波器的系统增益
短句来源
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A new adaptive Kalman filter is presented for the single output system with unknown noise statistics. By a time series analysis, a new and simpler estimation algorithm for the gain of the steady-state optimal Kalman filter is given. A new adaptive Kalman filtering algorithm is also given for identifying the parameters of moving average (MA) model. An application to a radar tracking system is given to show the usefulness of the proposed new algorithms.

对于带未知噪声统计的单输出系统,本文提出了一种新的自适应Kalman滤波器,应用现代时间序列分析方法,基于ARMA新息模型的滑动平均(MA)参数的在线辨识,提出了稳态最优Kalman滤波器增益估计的一种新算法,比Mehra的算法简单。同时还提出了辨识滑动平均(MA)模型参数的一种新的自适应Kalman滤波算法。此外,给出了在雷达跟踪系统中的应用,且仿真结果说明了本文算法的有效性。

Using the modern time series analysis, based on the ARMA innovation model. this paper presents a new algorithm of steady-state Kalman filter gain. which can handle systems with the correlated model and observation noises, and also can handle systems with singular and/or unstable state transition matrix. A simulation example shows its usefulness.

用现代时间序列分析方法,基于ARMA新息模型,提出了稳态Kalman滤波器增益阵的一种新算法。可处理模型噪声与观测噪声相关的系统,也可处理带奇异的和/或不稳定状态转移阵的系统。仿真例子说明了其有效性。

By using the modern time series analysis method and based on the ARMA innovation model,two new algorithms of steady state Kalman filter gain are presented,and their equivalence is proved.The self tuning Kalman filters can be implemented by using a recursive identifier of parameters for the ARMA innovation model,in conjunction with the new algorithms.A simulation example shows usefulness of the proposed algorithms.

应用现代时间序列分析方法,基于ARMA新息模型,提出了稳态Kalman滤波器增益的两种简单的新算法,并证明了它们的等价性.应用ARMA新息模型参数的递推辨识器伴随新算法,可实现自校正Kalman滤波器.仿真例子说明了其有效性.

 
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