Description: The purpose of this paper is to provide a practical introduction to the discrete Kalman
filter. This introduction includes a description and some discussion of the basic
discrete Kalman filter, a derivation, description and some discussion of the extended
Kalman filter, and a relatively simple (tangible) example with real numbers &
results.-The purpose of this paper is to provide a pra ctical introduction to the discrete Kalman fil ter. This introduction includes a description and some discussion of the basic discrete Kalma n filter, a derivation. description and some discussion of the extende d Kalman filter. and a relatively simple (tangible) example wit h real numbers Platform: |
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Author:上将 |
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Description: 离散随机线性系统的卡尔曼滤波。
其中13lman.c是卡尔曼滤波函数，4rinv.c是滤波函数中用到的矩阵求逆函数，13lman0.c是主程序。-discrete stochastic linear Kalman filtering system. 13lman.c which is the Kalman filter function, 4rinv.c filtering function is used in the matrix inversion function, is the main program 13lman0.c. Platform: |
Size: 2048 |
Author:通信学生 |
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Description: 此为时间离散点上采样数据进行的卡尔曼滤波算法-this time of discrete points on the sampling data for the Kalman Filter Platform: |
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Author:GaleWing |
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Description: 好东西 ，是关于离散卡尔曼滤波的。大家看了就知道了-good stuff is on the discrete Kalman filter. We read on to know the Platform: |
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Author:wybiao |
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Description: 硕士学位论文捷联惯性系统初始对准研究
惯导系统的初始对准是影响系统使用性能的关键技术之一，对准的精度与速度直接关系到惯性统的精度与启动特性。对卡尔曼滤波及其在初始对准中的应用进行了研究。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提出了适用于舰载捷联惯性系统的动基座对准的2通道10个状态变量和2通道12个状态变量的系统动态模型，并建了相应的速度匹配和位置匹配量测模型。
-master's degree thesis SINS initial alignment study INS initial alignment is affecting system performance one of the key technologies, the alignment precision and speed is directly related to the precision inertial reunification with the startup characteristics. The Kalman filter and the initial alignment of the study. First introduced the theory of Kalman filtering background, and then reasoned a discrete Kalman filter equations, also for the state of discrete equations apply to the carrier SINS System Moving Base Alignment of two channels 10 state variables and two 12-channel system state variables dynamic model and built a corresponding speed matching and position matching measurement model. Platform: |
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Author:王琴 |
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Description: The purpose of this paper is to provide a practical introduction to the discrete Kalman
filter. This introduction includes a description and some discussion of the basic
discrete Kalman filter, a derivation, description and some discussion of the extended
Kalman filter, and a relatively simple (tangible) example with real numbers &
results.-The purpose of this paper is to provide a pra ctical introduction to the discrete Kalman fil ter. This introduction includes a description and some discussion of the basic discrete Kalma n filter, a derivation. description and some discussion of the extende d Kalman filter. and a relatively simple (tangible) example wit h real numbers Platform: |
Size: 221184 |
Author:上将 |
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Description: 卡尔曼滤波的vb源程序(现设线性时变系统的离散状态防城和观测方程)-Kalman Filter vb source (now based linear time-varying systems of discrete state Fangcheng and observation equation) Platform: |
Size: 1024 |
Author:爱德 |
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Description: 1960年，卡尔曼发表了他著名的用递归方法解决离散数据线性滤波
问题的论文。从那以后，得益于数字计算技术的进步，卡尔曼滤波器
已成为推广研究和应用的主题，尤其是在自主或协助导航领域。-In 1960, Kalman published his famous recursive solution using discrete data linear filtering problem papers. Since then, figures to benefit from advances in technology, Kalman filter has become the promotion of research and application of the theme, especially in the field of autonomous or assisted navigation. Platform: |
Size: 409600 |
Author:kysuli |
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Description: documentation for optimal filtering toolbox for mathematical software
package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter
and unscented Kalman filter for discrete time state space models. Also included in the toolbox
are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which
can be used to smooth the previous state estimates, after obtaining new measurements. The usage
and function of each method are illustrated with five demonstrations problems.
1
-documentation for optimal filtering toolbox for mathematical softwarepackage Matlab. The methods in the toolbox include Kalman filter, extended Kalman filterand unscented Kalman filter for discrete time state space models. Als Platform: |
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Author:eestarliu |
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Description: documentation for optimal filtering toolbox for mathematical software
package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter
and unscented Kalman filter for discrete time state space models. Also included in the toolbox
are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which
can be used to smooth the previous state estimates, after obtaining new measurements. The usage
and function of each method are illustrated with five demonstrations problems.
1-documentation for optimal filtering toolbox for mathematical softwarepackage Matlab. The methods in the toolbox include Kalman filter, extended Kalman filterand unscented Kalman filter for discrete time state space models. Als Platform: |
Size: 640000 |
Author:eestarliu |
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Description: 经典kalman滤波程序，是初学者参考很好的例子-The purpose of this paper is to provide a practical introduction to the discrete Kalman
filter. This introduction includes a description and some discussion of the basic
discrete Kalman filter, a derivation, description and some discussion of the extended
Kalman filter, and a relatively simple (tangible) example with real numbers &
results.
Platform: |
Size: 1024 |
Author:何河 |
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Description: Object-based framework for performing Kalman filtering for discrete time systems or continuous-discrete hybrid systems. Includes code for the classical Kalman filter for linear systems, the extended Kalman filter (EKF), and the more recent unscented Kalman filter (UKF). Both linear and non-linear noise in the system and observation are permitted. Platform: |
Size: 22528 |
Author:mitko |
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Description: THIS PROGRAM IS FOR IMPLEMENTATION OF DISCRETE TIME PROCESS UNSCENTED KALMAN FILTER FOR GAUSSIAN AND LINEAR STOCHASTIC DIFFERENCE EQUATION. Platform: |
Size: 2048 |
Author:Kamdulong |
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Description: Estimation, Control, and the Discrete Kalman Filter
By:Donald E. Catlin
-Estimation, Control, and the Discrete Kalman Filter
By:Donald E. Catlin
Platform: |
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Author:Gomaa Haroun |
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Description: 介绍了Kalman滤波器是一种线性的离散时间有限维系统，对kalman滤波算法公式进行了详细的推导-It introduced the Kalman filter is a finite-dimensional linear discrete-time system, kalman filtering algorithm formula derived in detail Platform: |
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Author:yjq |
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Description: 5.4.2 Kalman滤波器的设计
这一节将讨论如何使用控制系统工具箱进行Kalman滤波器的设计和仿真。 考虑下面的离散系统：
x［n+1］=Ax［n］+B(u［n］+w［n］) (5.9)
y［n］=Cx［n］ (5.10)
其中, w［n］是在输入端加入的高斯噪声。 状态矩阵参数分别为
A = ［1.1269-0.49400.1129
1.0000 0 0
0 1.0000 0］;
B = ［-0.3832
0.5919
0.5191］;
C = ［1 0 0］;
我们的目标是设计Kalman滤波器, 在给定输入u［n］和带噪输出测量值
yv［n］=Cx［n］+v［n］的情况下估计系统的输出。 其中, v［n］是高斯白噪声。
1） 离散Kalman滤波器
上述问题的稳态Kalman滤波器方程如下：
测量值修正计算(Design of 5.4.2 Kalman filter
This section will discuss how to use the control system toolbox to design and simulate Kalman filters. Consider the following discrete systems:
X [n+1] =Ax [n] +B (u [n] +w [n]) (5.9)
Y [n] =Cx [n] (5.10)
Among them, w [n] is the Gauss noise added at the input end. State matrix parameters are respectively
A = [1.1269-0.49400.1129
1
1];
B = [-0.3832
Zero point five nine one nine
0.5191];
C = [100];
Our goal is to design Kalman filters at given input u [n] and noise output measurements.
The output of the system is estimated in the case of YV [n] =Cx [n] +v [n]. Among them, v [n] is Gauss white noise.
1) discrete Kalman filter
The steady-state Kalman filter equations for the above problems are as follows:
Correction calculation of measurement value) Platform: |
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Author:圆圆圈圈m |
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