matlab_ukf_utilities

代码说明：

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
....................\chi_square_density.m,402,2005-04-28
....................\chi_square_mass.m,360,2005-04-28
....................\chi_square_to_gauss.m,678,2006-01-24
....................\Contents.m,4399,2006-02-09
....................\demo_bearing_only.m,4168,2006-01-05
....................\demo_chi_square.m,722,2006-01-05
....................\demo_ekf_filter.m,5217,2005-12-06
....................\demo_kmeans.m,531,2005-11-29
....................\demo_particle_filter.m,3962,2005-06-09
....................\demo_unscented_filter.m,4058,2005-04-28
....................\distance_bhattacharyya.m,772,2005-12-08
....................\distance_KLD.m,930,2005-12-08
....................\distance_KLD_symmetric.m,737,2005-12-08
....................\distance_mahalanobis.m,466,2005-07-29
....................\distance_normalised.m,997,2006-01-05
....................\dist_sqr.m,736,2005-10-11
....................\dist_sqr_.m,862,2005-10-11
....................\dist_sqr_v2.m,812,2005-04-28
....................\EKF_update.m,2337,2005-06-09
....................\ellipse_mass.m,540,2006-02-09
....................\ellipse_sigma.m,506,2006-02-09
....................\gauss_evaluate.m,1134,2005-10-18
....................\gauss_likelihood.m,1229,2005-04-28
....................\gauss_regularise.m,363,2005-04-28
....................\gauss_samples.m,408,2005-04-28
....................\index_table.m,1193,2005-07-29
....................\inv_posdef.m,337,2005-04-28
....................\KF_update.m,298,2005-06-09
....................\KF_update_cholesky.m,673,2005-04-28
....................\KF_update_IEKF.m,1472,2005-04-28
....................\KF_update_joseph.m,755,2006-02-09
....................\KF_update_simple.m,633,2005-04-28
....................\kmeans.m,1224,2005-11-24
....................\line_plot_conversion.m,835,2005-04-28
....................\multivariate_gauss.m,406,2005-04-28
....................\notes.txt,478,2006-01-05
....................\numerical_Jacobian.m,1406,2005-04-28
....................\pi_to_pi.m,594,2005-04-28
....................\readme.txt,2710,2005-06-09
....................\repcol.m,385,2005-06-09
....................\reprow.m,336,2005-06-09
....................\repvec.m,339,2005-04-28
....................\sample_mean.m,1203,2005-12-08
....................\sample_mean_weighted.m,973,2005-12-08
....................\sigma_ellipse.m,411,2006-01-27
....................\sqrt_posdef.m,1017,2006-02-09
....................\stratified_random.m,338,2005-08-31
....................\stratified_resample.m,795,2005-04-28
....................\transform_to_global.m,479,2005-04-28
....................\transform_to_relative.m,462,2005-04-28
....................\uniform_random.m,293,2005-04-28
....................\unscented_transform.m,3713,2005-04-28
....................\unscented_update.m,3707,2005-06-09