Description: EKF Extended Kalman Filter for nonlinear dynamic systems
[x, P] = ekf(f,x,P,h,z,Q,R) returns state estimate, x and state covariance, P
for nonlinear dynamic system:
x_k+1 = f(x_k)+ w_k
z_k = h(x_k)+ v_k
where w ~ N(0,Q) meaning w is gaussian noise with covariance Q
v ~ N(0,R) meaning v is gaussian noise with covariance R
Inputs: f: function handle for f(x)
x: a priori state estimate
P: a priori estimated state covariance
h: fanction handle for h(x)
z: current measurement
Q: process noise covariance
R: measurement noise covariance
Output: x: a posteriori state estimate
P: a posteriori state covariance
Example:
To Search:
File list (Check if you may need any files):
ekf2\ekf\ekf.m
....\ekf.m
....\ekf
ekf2
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