搜索资源列表
KF_COMPARE_CODE
- 两种滤波方法的跟踪精度比较：即扩展卡尔曼滤波和无迹卡尔曼滤波的比较（EKF 与UKF）(Comparing the tracking accuracy of the two filtering methods: the comparison between the extended Calman filter and the untracked Calman filter (EKF and UKF))
19-史子纬-作业6
- 卡尔曼滤波（Kalman filtering）一种利用线性系统状态方程，通过系统输入输出观测数据，对系统状态进行最优估计的算法。由于观测数据中包括系统中的噪声和干扰的影响，所以最优估计也可看作是滤波过程。(Calman filter (Kalman filtering) uses the state equation of linear system and optimally estimates the state of the system by input and output obser
lvbo
- MTI的AHRS解算程序，包含互补滤波的一阶、二阶和卡尔曼滤波程序。(The AHRS solution program of MTI includes the first, two order and Calman filter programs of complementary filtering)
Pf1
- 粒子卡尔曼滤波程序，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
pf2
- 粒子卡尔曼滤波程序2，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
pf3
- 粒子卡尔曼滤波程序3，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
upf_demos
- 无味变换粒子卡尔曼滤波程序，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
2008_7387
- 粒子卡尔曼滤波文献，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
2009_5781
- 粒子卡尔曼滤波文献资料，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
2009_6309
- 粒子卡尔曼滤波文献，可以实现高效非线性滤波算法，赶快下载吧。(Particle Calman filter program, can achieve efficient nonlinear filtering algorithm, quickly download it.)
2012_81_2_14_S0094576512003293
- 一篇粒子卡尔曼滤波参考文献，可以实现高效非线性滤波算法，赶快下载吧。(A particle Calman filter reference, can achieve efficient nonlinear filtering algorithm, quickly download it.)
abr滤波代码
- abr滤波算法实现（卡尔曼滤波的简化算法）(Implementation of ABR filtering algorithm Simplified algorithm of Calman filter)
P2_KalmanFilter_Example
- 卡尔曼滤波（Kalman filtering）一种利用线性系统状态方程，通过系统输入输出观测数据，对系统状态进行最优估计的算法。由于观测数据中包括系统中的噪声和干扰的影响，所以最优估计也可看作是滤波过程。 斯坦利·施密特(Stanley Schmidt)首次实现了卡尔曼滤波器。卡尔曼在NASA埃姆斯研究中心访问时，发现他的方法对于解决阿波罗计划的轨道预测很有用，后来阿波罗飞船的导航电脑使用了这种滤波器。 关于这种滤波器的论文由Swerling (1958), Kalman (1960)与 Ka
3
- 本程序主要针对笛卡尔滤波程序进行仿真，主要为目标运动的轨迹估计，相对于之前的程序这次在观测信号中含有距离、速度信息！ 程序正确完整，适合了解卡尔曼的同事学习交流！(This program is mainly for Descartes filtering program simulation, mainly for target motion trajectory estimation, compared with previous procedures, this observation c