Description: 本程序是用matlab开发的扩展Kalman Filter-this procedure is used Matlab development of the extended Kalman Filter Platform: |
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Author:sun |
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Description: 文件包含有5项内容：
一、扩展卡尔曼滤波EKF
二、去偏转换卡尔曼滤波CMKF
三、最小二乘拟和的方法
四、最小二乘、EKF、CMKF的比较
五、野值剔除算法
用MATLAB实现了这些具体算法和要求
-document contains five elements : an extended Kalman Filter EKF two, Partial conversion to CMKF three Kalman filtering, and the least squares method to be four, least squares, EKF. Comparison of five CMKF, excluding outliers algorithm in MATLAB these algorithms and specific requirements Platform: |
Size: 226304 |
Author:jiji |
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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: ：介绍了扩展卡尔曼滤波算法和无迹变换(unscented transformation，UT)算法，并对扩展卡尔曼滤波算法(EKF)和无
迹卡尔曼滤波算法(UKF)进行比较，阐明了UKF优于EKF。在此基础上，提出了一种基于Unscented变换(uT)的高斯和滤
波算法，该算法首先通过合并准则得到适当个数的混合高斯模型，逼近系统中非高斯噪声的概率密度-: Introduction of the extended Kalman filter algorithm and unscented transform (unscented transformation, UT) algorithm, the extended Kalman filter algorithm (EKF) and unscented Kalman filter (UKF) for comparison to clarify the UKF is superior to EKF. On this basis, we propose an approach based on Unscented Transform (uT) and the Gaussian filtering algorithm, which first of all, by merging the appropriate number of criteria to be a mixture of Gaussian model, which was close to the system of the Central African Gaussian noise probability density Platform: |
Size: 205824 |
Author:lyh |
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Description: 目标跟踪的扩展卡尔曼滤波算法主函数的文件是：kal_demo.m
近似网格滤波的主函数文件是：bayes_demo.m
近似网格滤波划分网格的方法是：以目标上一个时刻的位置作为中心进行网格的划分，每个网格大小为1，总的区域为5*5
改进后算法的主函数文件是：trackiing_demo.m-Target tracking extended Kalman filter algorithm is the main function of the document: kal_demo.m approximate mesh filter paper is the main function: bayes_demo.m approximate mesh filter into the grid method is: in order to target the location of a moment as the central to carry out the division of the grid, each grid size of 1, with a total area of 5* 5 to improve the algorithm Platform: |
Size: 138240 |
Author:Lin |
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Description: 介绍了几个基于EKF扩展卡尔曼滤波的例子，可以帮助更好的理解扩展卡尔曼滤波-Introduced a few based on extended Kalman filter EKF example, can help a better understanding of extended Kalman filter Platform: |
Size: 16384 |
Author:yueyang |
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Description: 一个扩展卡尔曼滤波的matlab程序,是个不错的学习例子-An extended Kalman filter matlab procedures, be a good learning example Platform: |
Size: 94208 |
Author:tinyli |
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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: The state space model is nonlinear and is input to the function along with the current measurement. The function performs the extended Kalman filter update and returns the estimated next state and error covariance Platform: |
Size: 1024 |
Author:sofi |
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Description: 卡尔曼滤波原理及应用—MATLAB仿真主要介绍数字信号处理中的卡尔曼（Kalman）滤波算法及在相关领域应用。全书共7章。第1章为绪论。第2章介绍MATLAB算法仿真的编程基础。第3章介绍线性Kalman滤波。第4章讨论扩展Kalman滤波，并介绍其在目标跟踪和制导领域的应用和算法仿真。第5章介绍UKF滤波算法，同时也给出其应用领域内的算法仿真实例。第6章介绍了交互多模型Kalman滤波算法。第7章介绍Simulink环境下，如何通过模块库和S函数构建Kalman滤波器，并给出了系统是线性和非线性两种情况的滤波器设计方法(Principle and Application of Kalman Filter - MATLAB simulation mainly introduces Kalman filtering algorithm in digital signal processing and its application in related fields. The book consists of 7 chapters. The first chapter is the introduction. The second chapter introduces the programming foundation of MATLAB algorithm simulation. The third chapter introduces linear Kalman filtering. Chapter 4 discusses the extended Kalman filter, and introduces its application and algorithm simulation in the field of target tracking and guidance. The fifth chapter introduces the UKF filtering algorithm, and gives an example of algorithm simulation in its application area. The sixth chapter introduces the interacting multiple model Kalman filtering algorithm. Chapter 7 introduces how to construct Kalman filter by module library and S-function in Simulink environment, and gives the design method of Kalman filter for both linear and nonlinear systems.) Platform: |
Size: 13403136 |
Author:jianjian健健 |
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