文件名称:P2_KalmanFilter_Example
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卡尔曼滤波(Kalman filtering)一种利用线性系统状态方程,通过系统输入输出观测数据,对系统状态进行最优估计的算法。由于观测数据中包括系统中的噪声和干扰的影响,所以最优估计也可看作是滤波过程。
斯坦利·施密特(Stanley Schmidt)首次实现了卡尔曼滤波器。卡尔曼在NASA埃姆斯研究中心访问时,发现他的方法对于解决阿波罗计划的轨道预测很有用,后来阿波罗飞船的导航电脑使用了这种滤波器。 关于这种滤波器的论文由Swerling (1958), Kalman (1960)与 Kalman and Bucy (1961)发表
卡尔曼滤波,非常66666666666666666666666666的程序(Calman filter (Kalman filtering) uses the state equation of linear system and optimally estimates the state of the system by input and output observation data. Because the observation data includes the influence of noise and interference in the system, the optimal estimation can also be considered as a filtering process.
Stanley Schmidt (Stanley Schmidt) realized the Calman filter for the first time. When Calman visited the NASA Ames Research Center, he found that his method was very useful for solving Apollo plan's orbit prediction. Later, Apollo's navigation computer used this filter. Papers on this filter are published by Swerling (1958), Kalman (1960) and Kalman and Bucy (1961)
Calman filter, a very good program)
斯坦利·施密特(Stanley Schmidt)首次实现了卡尔曼滤波器。卡尔曼在NASA埃姆斯研究中心访问时,发现他的方法对于解决阿波罗计划的轨道预测很有用,后来阿波罗飞船的导航电脑使用了这种滤波器。 关于这种滤波器的论文由Swerling (1958), Kalman (1960)与 Kalman and Bucy (1961)发表
卡尔曼滤波,非常66666666666666666666666666的程序(Calman filter (Kalman filtering) uses the state equation of linear system and optimally estimates the state of the system by input and output observation data. Because the observation data includes the influence of noise and interference in the system, the optimal estimation can also be considered as a filtering process.
Stanley Schmidt (Stanley Schmidt) realized the Calman filter for the first time. When Calman visited the NASA Ames Research Center, he found that his method was very useful for solving Apollo plan's orbit prediction. Later, Apollo's navigation computer used this filter. Papers on this filter are published by Swerling (1958), Kalman (1960) and Kalman and Bucy (1961)
Calman filter, a very good program)
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文件名 | 大小 | 更新时间 |
---|---|---|
P2_KalmanFilter_Example.m | 2740 | 2017-06-29 |