卡尔曼滤波

基于卡尔曼滤波的INTERNET蠕虫预警系统研究

Improving Internet Worm Warning System Based on Kalman Filter

迭代扩展卡尔曼滤波用于实时GPS数据处理

Iterated Extended Kalman Filter Application to Real time GPS Data Processing

神经网络优化动态GPS卡尔曼滤波算法研究

Study of Neural Network optimizes Dynamic GPS Kalman Filtering Algorithm

新型GPS动态定位自适应卡尔曼滤波方法

A new self-adaptive Kalman filtering method for GPS kinematic positioning

卡尔曼滤波可靠性分析及其在动态GPS定位中的应用

Reliability Analysis for Kalman Filtering and Its Application in Kinematic GPS Positioning

利用卡尔曼滤波快速确定GPS整周模糊度的研究

Study on Fast GPS Integer Ambiguity Resolution by Kalman Filter

基于MATLAB的卡尔曼滤波法参数辨识与仿真

Kalman Filter Parameter Identification and Emulate Based on Matlab

GPS动态定位的强跟踪卡尔曼滤波研究

Modified Strong Tracking Kalman Filter and Its Application in GPS Kinematic Positioning for Moving Vehicles

流动注射pH梯度技术&卡尔曼滤波分光光度法同时测定锶和钡

Simultaneous Determination of Barium and Strontium by pH Gradient Technique in FIA and Kalman Filtering Spectrophotometric Method

一种新的车载DR系统自适应卡尔曼滤波模型

New Modified Adaptive Extended Kalman Filter of DR System for Land Vehicle Navigation

卡尔曼滤波在多维AR序列建模中的应用

Application of Kalman filter in modeling multi-dimensional ar series

基于无轨迹卡尔曼滤波神经网络的SINS初始对准方法

Application of Neural Network Based on Unscented Kalman Filter in SINS Alignment

速度误差反馈调平可以达到较高的精度，但是快速性不如卡尔曼滤波和H∞滤波；

The velocity error linear feedback can obtain high precision , but the speediness is lower than Kalman filter andH ∞ filter .

通过MonteCarlo仿真，给出了基于双星定位的扩展卡尔曼滤波算法对目标的弹道参数估计的结果。

Trajectory parameters EKF estimation result based on two satellites positioning is given by Monte Carlo simulation .

如果GPS信号受到干扰或者车辆做大幅度机动时，卡尔曼滤波会有较大的误差。

If GPS is disturbed or the vehicle moves quickly , the errors of KF ( Kalman Filter ) are quite big .

非线性估计的Sigma点卡尔曼滤波方法

Sigma Point Kalman Filter for Non - linear Estimation

针对模糊控制技术进行了无人机控制算法研究，对于姿态测量信号以及导航信息，利用了卡尔曼滤波的方式进行了数据处理，并进行了GPS／惯性导航的组合导航技术的研究；

Using the fuzzy control on the control methods , and apply the KALMAN filter wave on the measured information and combined navigation ;

Sigma点卡尔曼滤波及其应用

Sigma-point Kalman filter and its application

应用卡尔曼滤波方法，对采用GPS姿态测量信息对惯性导航系统的误差修正能力进行分析和仿真。

By adopting the Kalman filtering method , the capability of correcting the error of inertial navigation system using GPS attitude information is analyzed and simulated .

基于卡尔曼滤波的动态OD矩阵估计

Kalman Filtering Based Dynamic OD Matrix Estimation

研究了利用GPS预报电离层TEC和监测电离层扰动的方法。在分析电离层时空相关性的基础上，利用离散系统的卡尔曼滤波方程对电离层TEC进行了预报；

Lastly , study the method of predicting TEC and scouting ionospheric disturbance by GPS data .

采用一种新的自适应卡尔曼滤波多用户检测算法估计CDMA系统多用户接收器的最优判决向量，高性能盲自适应多用户检测算法。

A new multiuser detector based on adaptive Kalman filter is described to estimate the optimal decision vector of CDMA multiuser receiver .

分析了现有机动目标数学模型及其卡尔曼滤波算法，并用数字信号处理器（DSP）对一个实际算法进行了实验。

In this paper , the writers analyse the current maneuvering target models and their Kalman filtering algorithms , and experiment on a practical algorithm with DSP .

介绍了一种新的自适应卡尔曼滤波算法，该法当R（或Q）已知时可以准确地估计出Q（或R）。

A new algorithm of adaptive Kalman filter is introduced which can estimate Q ( or R ) accurately when R ( or Q ) is known .

根据集合卡尔曼滤波产生的必要条件，介绍了集合卡尔曼滤波整合动态数据和3D地震数据的基本原理。

According to the application conditions of the Ensemble Kalman , we introduce the basic principles of integration of dynamic data and 3D seismic data using the Ensemble Kalman Filter .

由于传统卡尔曼滤波算法模型建立的近似性，本文讨论了自适应滤波算法和BP神经网络理论，它们是对传统卡尔曼滤波算法的改进和突破。

Due to the model 's inexactitude of traditional Kalman filter , we discuss adaptive filtering and BP neural network which are the improvement of traditional Kalman filter .

该算法利用卡尔曼滤波实现了CDMA蜂窝网系统和GPS定位数据融合，提出高移动目标的事实上的位精度。

The location data fusion of CDMA wireless system and PS is implemented using the Kalman filter , which improves the position accuracy of mobile station .

主要内容包括：将获取的GPS数据转换为世界坐标然后进行卡尔曼滤波，提高了坐标的精确性；

The work contents are mainly composed of : translating the GPS data to Cartesian coordinates and then using the kalman filter to improve the precise of the coordinates ;

采用MeanShift和卡尔曼滤波相结合的目标跟踪算法对目标进行实时跟踪，并验证了该算法实时性较好，鲁棒性较高。

The combined algorithm of Mean Shift and Kalman Filter is used to track target . The algorithm has proved to be good real time and robust by large number of experiments .

提出适用于低成本捷联惯导系统的初始对准方法，即采用非线性对准模型和采样卡尔曼滤波（UnscentedKalmanFilter）进行状态估计。

An initial alignment method for low-cost SINS is proposed , which uses nonlinear error model and the unscented Kalman filter ( UKF ) .