由于状态和观测方程都是非线性的，故采用了扩展的卡尔曼滤波器。
Due to the nonlinearity of the state and measurement equations, the extended Kalman filter is used.
本文以T42数值预报产品为因子，用卡尔曼滤波方法建立可更新系数的预报方程作南京和芜湖的温度预报。
The temperature forecasting equation with renewed coefficients are set up by using Kalman filter technique based on the factors of T42 productions for forecasting in Nanjing and Wuhu.
同时利用卡尔曼滤波误差方程对自主导航算法进行误差分析，并将两种分析结果作比较。
At the same time, we use Kalman filter error equations in errors analysis for autonomous navigation algorithm, and compare the analysis results of the two methods.
扩展的卡尔曼滤波定位方法是一个常用的位置跟踪方法，但是在对非线性系统方程进行线性化近似过程中引入了线性化误差。
Extended Kalman Filter is an efficient tool for mobile robot position tracking, but it suffers from linearization errors due to linear approximation of nonlinear system equations.
本文运用卡尔曼滤波原理，提出了一种新的神经网络学习算法。该算法的学习速度是由带时间参数的里卡蒂微分方程来确定的。
In this paper, making use of Kalman filtering, we derive a new back-propagation algorithm whose learning rate is computed by Riccati difference equation.
首先介绍了卡尔曼滤波理论的应用背景，然后推导了离散卡尔曼滤波方程，并对连续系统的状态方程进行离散化。
At first, the application background of Kalman filter theory is introduced. Then, discrete Kalman filter equations are derived, and state equations of continuous system are discreted.
在建立目标机动模型与测量方程的基础上，运用修正增益扩展卡尔曼滤波（MGEKF）算法，实现对机动目标进行定位与跟踪。
On the basis of building target movement model and measuring equation, applying MGEKF algorithm, realizes the locating and tracking for mobile target.
第三章，建立了卫星轨道动力学模型，设计了GPS和运动方程组合的卡尔曼滤波器，并针对不同轨道高度的微小卫星进行了定位仿真。
In chapter 3, the orbit dynamics models are established, the Kalman Filter of the GPS and kinematics equation combined are designed, and simulations of different orbit Micro-satellite are done.
由于选择了新的机动加速度量，从而得出线性的状态方程，由机动指令的实时估计得到机动目标自适应跟踪卡尔曼滤波器。
A linear state equation is got from selection of maneuvering acceleration. The adaptivity of adaptive tracking Kalman filter is represented by estimation of maneuvering commander at real time.
卡尔曼滤波的主要思想，是用状态方程和量测方程描述线性动态系统。
The main idea of Kalman filtering is to describe the linear dynamic system using state equation and measurement equation.
结合实际重力仪的系统状态方程和系统量测方程，提出了级联卡尔曼滤波方法，并将其应用于重力异常畸变信号的校正处理中。
Combined with the system state equation and the measurement equation, a new method of the cascade Kalman filter is proposed and applied to the correction of gravity anomaly distortion.
首先介绍了卡尔曼滤波理论及相关技术，建立了系统卡尔曼滤波的状态方程和观测方程；
The Kalman filter theory is introduced and the dynamic error vector equation of the initial alignment is derived at the first.
对各方程序卡尔曼滤波，通过T -SFIMMA算法进行基于T - S模糊模型的自适应卡尔曼滤波计算，实现系统模型的实时跟踪与自动转换。
Kalman filter of the kind of equations was calculated with T-SFIMMA algorithm based on adaptive Kalman filter algorithm of T-S fuzzy model, realize the tracking and automatic switchover of models.
根据卡尔曼滤波新息过程的统计特点，将新息过程部分反馈到DR方程以抑制DR的误差发散。
Innovations of FKF are partly fed back to DR equations to restrain the accumulation of error according to the characteristic of innovations.
导出了卡尔曼滤波应用于GPS监测系统的状态方程和观测方程的纯量形式和矩阵形式，给出了系统的滤波方程。
This paper puts forward the state equation and observation equation in matrix and simple, and gives the system filtering equation when Kalman filtering is applied to the GPS monitoring system .
列出了对位置偏差估计的状态方程和测量方程，用加权的最小二乘估计和卡尔曼滤波算法，实现了定位和跟踪。
The state equation and detecting equation of the position error of moving target are built, the location and track to moving target is achieved by least-square estimation and Kalman filter algorithm.
本文基于NGMIMU九加速度计配置方案，利用卡尔曼滤波器抑制误差的累积，并且推导了卡尔曼滤波器的状态方程和预防方程。
To alleviate the accumulation error, a Kalman-filtering approach based on a nine-accelerometer configuration of NGMIMU is proposed. The state equation and estimation equation are also deduced.
提出了将三集总催化裂化反应动力学微分方程组转化为卡尔曼滤波状态方程的处理方法。
A method is proposed for converting the differential equations of three lumping kinetic model into the state equations of Kalman filter.
首先假设边坡滑坡体为刚体，建立边坡滑坡的动态模型，由此建立卡尔曼滤波的系统方程。
At first the dynamic model of the landsliding (forward model) is established on the assumption that the slope bodies are rigid.
在假定系统方程和过程方差的情况下，轮速信号的处理采用了卡尔曼滤波器的结构。
In this paper, measurement variance of the system is obtained with second order polynomial data fitling based on actual variance data of wheel speed signals.
把抽油机运动状态方程和卡尔曼滤波算法相结合，构造了一套适用的精确预测抽油机悬点速度的数学算法。
By combining the motion state equation with the Kalman filter algorithm, a mathematic calculation method for accurate prediction of the polished rod speed of the pumping unit is worked out.
将卡尔曼滤波技术应用于捷联惯导系统的初始对准研究，建立了系统的误差方程和量测方程，对系统的静基座初始对准进行了仿真研究。
By means of Kalman filter techniques, error equation and measure equation of SINS are presented. We made the simulation on initial alignment of navigation system on stationary base in the lab.
将卡尔曼滤波技术应用于捷联惯导系统的初始对准研究，建立了系统的误差方程和量测方程，对系统的静基座初始对准进行了仿真研究。
By means of Kalman filter techniques, error equation and measure equation of SINS are presented. We made the simulation on initial alignment of navigation system on stationary base in the lab.
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