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kalman Kálmán filter with delayed (outdated) information

We have a linear system with observation as follows:

$x(t+1)=Ax(t)+Bu(t)+w(t)$

$y(t)=Cx(t)+z(t)$

for given information $y(0\sim t)$, we can construct the dynamics of $\hat{x}(t)$ using the KalmanKálmán filter equations.

What if we are given information $y(0\sim t-N)$ where $N$ is a constant?

kalman filter with delayed (outdated) information

We have a linear system with observation as follows:

$x(t+1)=Ax(t)+Bu(t)+w(t)$

$y(t)=Cx(t)+z(t)$

for given information $y(0\sim t)$, we can construct the dynamics of $\hat{x}(t)$ using the Kalman filter equations.

What if we are given information $y(0\sim t-N)$ where $N$ is a constant?

Kálmán filter with delayed (outdated) information

We have a linear system with observation as follows:

$x(t+1)=Ax(t)+Bu(t)+w(t)$

$y(t)=Cx(t)+z(t)$

for given information $y(0\sim t)$, we can construct the dynamics of $\hat{x}(t)$ using the Kálmán filter equations.

What if we are given information $y(0\sim t-N)$ where $N$ is a constant?

Source Link

kalman filter with delayed (outdated) information

We have a linear system with observation as follows:

$x(t+1)=Ax(t)+Bu(t)+w(t)$

$y(t)=Cx(t)+z(t)$

for given information $y(0\sim t)$, we can construct the dynamics of $\hat{x}(t)$ using the Kalman filter equations.

What if we are given information $y(0\sim t-N)$ where $N$ is a constant?