matlab_ukf_utilities
所属分类:matlab编程
开发工具:matlab
文件大小:35KB
下载次数:100
上传日期:2011-03-05 22:05:53
上 传 者:
zhangjustice
说明: 卡尔曼滤波的一个典型实例是从一组有限的,对物体位置的,包含噪声的观察序列预测出物体的坐标位置及速度. 在很多工程应用(雷达, 计算机视觉)中都可以找到它的身影. 同时,卡尔曼滤波也是控制理论以及控制系统工程中的一个重要话题.
比如,在雷达中,人们感兴趣的是跟踪目标,但目标的位置,速度,加速度的测量值往往在任何时候都有噪声.卡尔曼滤波利用目标的动态信息,设法去掉噪声的影响,得到一个关于目标位置的好的估计。
(kalman ukf matlab)
文件列表:
matlab_ukf_utilities\chi_square_bound.m (691, 2005-04-28)
matlab_ukf_utilities\chi_square_density.m (402, 2005-04-28)
matlab_ukf_utilities\chi_square_mass.m (360, 2005-04-28)
matlab_ukf_utilities\chi_square_to_gauss.m (678, 2006-01-24)
matlab_ukf_utilities\Contents.m (4399, 2006-02-09)
matlab_ukf_utilities\demo_bearing_only.m (4168, 2006-01-05)
matlab_ukf_utilities\demo_chi_square.m (722, 2006-01-05)
matlab_ukf_utilities\demo_ekf_filter.m (5217, 2005-12-06)
matlab_ukf_utilities\demo_kmeans.m (531, 2005-11-29)
matlab_ukf_utilities\demo_particle_filter.m (3962, 2005-06-09)
matlab_ukf_utilities\demo_unscented_filter.m (4058, 2005-04-28)
matlab_ukf_utilities\distance_bhattacharyya.m (772, 2005-12-08)
matlab_ukf_utilities\distance_KLD.m (930, 2005-12-08)
matlab_ukf_utilities\distance_KLD_symmetric.m (737, 2005-12-08)
matlab_ukf_utilities\distance_mahalanobis.m (466, 2005-07-29)
matlab_ukf_utilities\distance_normalised.m (997, 2006-01-05)
matlab_ukf_utilities\dist_sqr.m (736, 2005-10-11)
matlab_ukf_utilities\dist_sqr_.m (862, 2005-10-11)
matlab_ukf_utilities\dist_sqr_v2.m (812, 2005-04-28)
matlab_ukf_utilities\EKF_update.m (2337, 2005-06-09)
matlab_ukf_utilities\ellipse_mass.m (540, 2006-02-09)
matlab_ukf_utilities\ellipse_sigma.m (506, 2006-02-09)
matlab_ukf_utilities\gauss_evaluate.m (1134, 2005-10-18)
matlab_ukf_utilities\gauss_likelihood.m (1229, 2005-04-28)
matlab_ukf_utilities\gauss_regularise.m (363, 2005-04-28)
matlab_ukf_utilities\gauss_samples.m (408, 2005-04-28)
matlab_ukf_utilities\index_table.m (1193, 2005-07-29)
matlab_ukf_utilities\inv_posdef.m (337, 2005-04-28)
matlab_ukf_utilities\KF_update.m (298, 2005-06-09)
matlab_ukf_utilities\KF_update_cholesky.m (673, 2005-04-28)
matlab_ukf_utilities\KF_update_IEKF.m (1472, 2005-04-28)
matlab_ukf_utilities\KF_update_joseph.m (755, 2006-02-09)
matlab_ukf_utilities\KF_update_simple.m (633, 2005-04-28)
matlab_ukf_utilities\kmeans.m (1224, 2005-11-24)
matlab_ukf_utilities\line_plot_conversion.m (835, 2005-04-28)
matlab_ukf_utilities\multivariate_gauss.m (406, 2005-04-28)
matlab_ukf_utilities\notes.txt (478, 2006-01-05)
matlab_ukf_utilities\numerical_Jacobian.m (1406, 2005-04-28)
matlab_ukf_utilities\pi_to_pi.m (594, 2005-04-28)
... ...
MatLab Utility Functions
------------------------
This collection are m-files I have written over the years that are reusable and I have found very useful in many projects. Some of them are listed below.
See Contents.m for a full alphabetic list of functions.
Kalman filter
-------------
KF_simple_update.m: Basic implementation of KF update.
KF_joseph_update.m: Numerically stable KF update (Joseph form).
KF_cholesky_update.m: Numerically stable KF update (best).
KF_IEKF_update.m: Iterated EKF update.
numerical_Jacobian.m: Compute an approximate Jacobian matrix for any non-linear function.
chi_square_bound.m: Compute a threshold for an innovation gate that encloses a specified probability mass.
inv_posdef: Compute the inverse of a positive-definite matrix
Demo filter application:
demo_ekf_filter.m
Unscented filter
----------------
Note, these implementations are of the basic unscented transform. For more sophisticated versions refer to the recent literature, eg:
Julier S.J. and Uhlmann J.K., Unscented Filtering and Nonlinear Estimation,
Proceedings of the IEEE, pp 401-422, Volume 92, Number 3, 2004.
Two general-purpose functions:
unscented_transform.m: Transform a mean and covariance through a non-linear function.
unscented_update.m: Perform an unscented Kalman update step with non-linear observe model.
Demo filter application:
demo_unscented_filter.m
Note: The new versions of unscented_transform.m and unscented_update.m require 'vectorised' models. To
operate with simple (non-vectorised) models, you may wish to use an old version of the functions. See the 'obsolete' directory and the '_old2' versions.
Particle filter
---------------
gauss_samples.m: Generate a set of samples from a multi-dimensional Gaussian.
gauss_likelihood: Compute the likelihood of a set of innovations.
gauss_regularise: Add jitter to particles after resampling according to Gaussian kernel.
stratified_random.m: Generate a sorted set of random numbers in range (0,1).
stratified_resample.m: Resample step for a particle filter.
sample_mean.m: Compute the mean and variance of a set of samples.
Demo filter application:
demo_particle_filter.m
2-D geometric transforms
------------------------
transform_to_global.m: Convert a local coordinate to the global frame.
transform_to_relative.m:Convert a global coordinate to a local frame.
pi_to_pi.m: Normalise a polar value to within plus-minus pi.
Animation Utilities
-------------------
line_plot_conversion.m: Convert an array of line-segments to a single polyline separated by NaNs.
sigma_ellipse.m: Create a polyline for an n-sigma covariance ellipse.
近期下载者:
相关文件:
收藏者: