搜索资源列表
KalmanAdptiveFilter
- 卡尔曼滤波器是用前一个估计值和最近一个观察数据估计信号的值,他是用状态方程和递推的方法进行估计,本例用来追踪一个5阶的FIR不确定的滤波器系数。-Kalman filter is to use the previous estimate and the most recent observation data to estimate the value of the signal, he is using the state equation and recursive estimation m
elecfans
- 卡尔曼滤波器扩展型号的非常有用,速度很快很强大-Kalman filter extended models are very useful, fast and very powerful
kalman1
- 卡尔曼滤波器的实现,对两个参量进行了滤波分析,效果比较理想-Realization of the Kalman filter, the filter of two parameters, the effect is more ideal
target-tracking-radar
- 下面是利用卡尔曼滤波的方法,实现雷达对目标的跟踪:一目标沿水平方向运动,起始位置为(-2000米,1000米),运动速度为15米/秒,扫描周期T=2秒, 米,采用蒙特卡洛方法对跟踪滤波器进行仿真,仿真次数为100次。-Below is the use of Kalman filtering method, to achieve the target tracking radar. Parameter :: a target in a horizontal direction, the start
test_radar2
- GBP1仿真,用于雷达跟踪,包含卡尔曼滤波器-GBP1 simulation
kalman
- 卡尔曼滤波器是一个“optimal recursive data processing algorithm(最优化自回归数据处理算法)”。-optimal recursive data processing algorithm