trackingKF does not output Kalman Gain

Question

Christian Busse 2021-9-17

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1455439-trackingkf-does-not-output-kalman-gain

评论： Prashant Arora 2023-11-21

采纳的回答： Prashant Arora

Hello,

why does trackingKF do not output the Kalman Gain?

Also, I think that an option to specify 'time-varying' or 'time-invariant' KF would be useful.

Best Regards

Christian

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Prashant Arora 2023-11-15

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1455439-trackingkf-does-not-output-kalman-gain#answer_1353307

编辑：Prashant Arora 2023-11-21

在 MATLAB Online 中打开

Hi,

As of R2024a, trackingKF does not output Kalman gain. We will consider this enhancement in the future releases.

As a workaround, you can compute Kalman gain using the output of the residual method.

predict(kf);
[r, S] = residual(kf, z);
H = kf.MeasurementModel;
P = kf.StateCovariance;
kalmanGain = P*H'/S;

Hope this helps.

Prashant

2 个评论
显示无隐藏无

Christian Busse 2023-11-20

Hello, thanks for the response.

My workaround looks similar:

S = H*P*H' + R;

B = H*P';

K = (S \ B)';

Do you think both approaches are equal or maybe the other is numerically more robust/efficient in MATLAB?

Prashant Arora 2023-11-21

在 MATLAB Online 中打开

Hi Christian,

Your approach looks equivalent to me.

You could consider modifying it a bit to reduce one transpose operation. However, I don't believe its going to have any noticeable impact on performance.

S = H*P*H' + R;
B = P*H';
K = B/S;

The only reason to use "residual" method would be to extend the same method to other Gaussian filters such as trackingEKF and trackingUKF. Internally, trackingEKF and trackingUKF also use numerically robust approach to compute the "S" (innovation covariance) using square root implementation. However, trackingKF is still plain vanilla (no square root) as of R2024a. So, your workaround looks equivalent trackingKF. We'll consider enhancing trackingKF in a future release to also use square-root implementation.

Hope this helps.

请先登录，再进行评论。