Two Kalman filters were used in this method.
该方法使用了两步卡尔曼滤波。
An algorithm of adaptive fuzzy Kalman filtering is presented.
提出了一种模糊自适应卡尔曼滤波算法。
The fourth chapter is about kalman trackers and an improvement.
第四章讨论了改进的卡尔曼跟踪滤波器。
Method of Kalman predict is discussed in terms of tracing moving object.
针对目标跟踪，本文探讨了卡尔曼预测的方法。
The application of Kalman filter in potential titration analysis is studied.
本文研究卡尔曼滤波在电位滴定分析法中的应用。
It utilizes extended Kalman filtering to carry out heterogeneous sensor fusion.
采用扩展卡尔曼滤波实现异质传感器融合。
The paper provides a new algorithm by introducing GM (1, 1) into Kalman filter .
针对这一问题，提出了一种基于GM （1， 1）模型的跟踪卡尔曼滤波方法。
With the algorithm of extend Kalman filter, the target motion analysis is discussed.
运用扩展卡尔曼滤波算法，研究了该系统的目标运动分析问题。
Kalman filtering is an optimum filtering employing the norm of minimum mean square error.
卡尔曼滤波采用最小均方误差准则，是一种最优滤波。
This is a simple demonstration of the Kalman filtering process, and they hope to help everyone.
这是一个简单的卡尔曼滤波演示程序，希望对大家有所帮助。
A time domain recursive low pass filtering algorithm based on Kalman filtering theory is analyzed.
分析了一种基于卡尔曼滤波理论的时域递归低通滤波算法。
Kalman filter is used to predict and track markers, making the tracking of markers more veracious.
利用卡尔曼滤波算法进行标记点预测和跟踪，提高了跟踪的准确性。
Due to the nonlinearity of the state and measurement equations, the extended Kalman filter is used.
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。
Therefore a new method of Kalman Filters used in phase unwrapping and noise restraining is proposed.
并提出了卡尔曼滤波在相位解缠与噪声抑制中的一种新算法。
The improvement of Kalman filtering in digital protection is introduced in order to suit the application.
介绍数字保护中卡尔曼滤波算法的一种改进，使它更适合实现。
The traditional method of Kalman filter for passive sonar target track association is limited in practice.
传统的目标航迹关联方法卡尔曼滤波法在实际应用时有局限性。
This paper investigates the application of adaptive Kalman filter in Moving Satellite Communication System.
研究了自适应卡尔曼滤波技术在移动卫星通讯系统中的应用。
The two-stage Kalman filter is excellent than standard Kalman filter in the presence of unknown random bias.
当动力学模型存在未知的随机系统偏差时，两阶段卡尔曼滤波要优于标准卡尔曼滤波。
This paper introduces and analyzes the application of the least square method and Kalman filter in time prediction.
介绍和分析了最小二乘和卡尔曼滤波方法在时间预报中的应用。
This paper introduces an algorithm of adaptive Kalman filter and its microcomputer software for extracting EEG signal.
本文介绍了一种提取脑电信号的自适应卡尔曼滤波算法及其微机处理软件。
X direction average error of object tracing using Kalman forecast is analyzed, and track and search range are estimated.
分析了采用卡尔曼预测进行目标跟踪引起的误差、估计了运动轨迹和搜索范围。
The main idea of Kalman filtering is to describe the linear dynamic system using state equation and measurement equation.
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。
Utilizing the wheel speed signals and applying the Kalman filter technology, the wheel angular acceleration is calculated.
利用车轮角速度信号，应用卡尔曼滤波技术来计算车轮角加速度信号。
Satisfactory results were achieved by using the extended Kalman filtering iterative algorithm for on-line state estimation.
用推广卡尔曼滤波迭代算法进行状态实时估计取得令人满意的结果。
Extended Kalman Filter (EKF) and converted measurement Kalman Filter (CMKF) have been widely used in radar target tracking.
在雷达目标跟踪中，扩展卡尔曼滤波(ekf)和转换坐标卡尔曼滤波(CMKF)得到了广泛的应用。
When the data were processed with Kalman filtering method, the gross errors could be found in the forecasting residual vector.
用卡尔曼滤波方法进行数据处理时，观测值中的粗差将在预测残差向量中得到反映。
Kalman filter is a linear minimum variance state estimator, and it combined array antenna and multiuser detection effectively.
卡尔曼滤波是一种线性最小方差状态估计，把它有效地结合阵列天线与多用户检测。
The whole algorithm conformation is very skilled. Because the number of kalman filter is lesser, algorithm is real-time, and robust.
算法构造巧妙，由于使用了较少的卡尔曼滤波器，算法实时性好，鲁棒性更好。
The Successive Orthogonalization Decentralized Kalman Filter (SODKF ) is a new method which is used for large system state estimation.
逐次正交化分布式卡尔曼滤波器是对大系统进行状态估计的一种新方法。
The element of template is probability of eigenvalue of target. These probability are acquire by a kalman filter group which had 48 kalman filters.
模板的元素取自目标特征值的概率，通过48个卡尔曼滤波器可以跟踪所有特征值的概率变化。
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