搜索资源列表
upf_demos
- 里面包含kalman，扩展kalman，无迹kalman，粒子滤波，无迹粒子滤波等源码的实现。-upf--The Unscented Particle Filter
matlab_utilities
- 粒子滤波、无迹粒子滤波算法程序，高斯混合模型参数设置等详细代码-Particle filter, unscented particle filter program, Gaussian mixture model parameter settings, and more code
upf
- 无迹粒子滤波例程，简单的跟踪应用。无杂波环境下的-Unscented particle filter routine, a simple tracking applications
particle-filter-visual-tracking
- 该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。
EKF_UKF_PF
- 扩展卡尔曼、无迹卡尔曼滤波、粒子滤波的算法对比，可以参考参考-Extended kalman, no trace kalman filter, the particle filter algorithm of contrast, hope that it help you.
ekf-ukf-pf
- 扩展卡尔曼滤波 无迹卡尔曼滤波 粒子滤波-EKF UKF PF
EKF-UKF-PF
- 扩展卡尔曼滤波，无迹卡尔曼滤波，粒子滤波三种算法的比较，matlab程序。-Extended Kalman filter, unscented Kalman filter, the comparison of the particle filter three algorithms, Matlab program.
Optimal-State-Estimation
- 状态估计领域权威书籍涉及例子的代码。涉及到卡尔曼滤波、扩展卡尔曼滤波、无迹卡尔曼滤波及粒子滤波等。-Matlab codes for the book named 《Optimal State Estimation》. These codes include Kalman filter, Extended Kalman filter, Uncented Kalman filter, and particle filter.
PF
- 对粒子滤波、无迹卡尔曼滤波以及扩展卡尔曼滤波的算法做了对比，表现了粒子滤波的良好特性。-Particle filtering, unscented Kalman filter and extended Kalman filter algorithm to do a comparison, the performance characteristics of a good particle filter.
EKF_UKF_PF_matlab
- 一个关于扩展卡尔曼滤波，粒子滤波和无迹卡尔曼滤波对比的matlab程序。-About the extended Kalman filter, particle filter and unscented Kalman filter matlab program comparison.
Belief-Condensation-Filtering-
- 自主导航系统中以卡尔曼滤波算法及其衍生算 法如扩展卡尔曼滤波、无迹卡尔 曼滤波、容积卡尔曼滤波 、鲁棒滤波或粒子滤波 等为信息处理的核心。-Autonomous navigation system with kalman filter algorithm and its derivatives Method such as extended kalman filtering, no trace, Carl Kal
UPF
- 无迹卡尔曼粒子滤波，有效的估计状态,ZHENHAO YONG(An unscented Calman particle filter is used to estimate the state effectively)
code _
- 粒子滤波PF，无迹粒子滤波UPF，卡尔曼滤波KF，扩展卡尔曼滤波EKF等例程与比较。建议下载，清晰明了(Particle filter PF, Untraced particle filter UPF, Kalman filter KF, extended Kalman filter EKF and other routines and comparisons.)
目标定位
- 研究目标跟踪的状态估计方法，最小二乘估计，Kalman滤波，扩展Kalman滤波，无迹Kalman滤波以及粒子滤波等，理论及MATLAB源程序。(The state estimation methods of target tracking, least square estimation, Kalman filtering, extended Kalman filtering, unscented Kalman filtering a