Learning the Kalman Filter

great!

Excellent!! Thank You.

Very helpful. Thanks!!

This is a very good example and shows how easy it is to apply the Kalman filter. It does, however, require some background knowledge. It would be nice to have a more complicated example with non-zero u and where H and A are not =1. Thanks Michael!

very good, I like the idea

Very fun. Very neat.

Nice work. It would be better if there is an example for vector state. Also it would be very cool if someone can put Kalman filter algorithm in simulink so that we can see the estimation of states dynamically. And of course, an extended kalman filter for nonlinear system would be also very useful.

A good try to explain something. Keep up the good work! There are, however, some mistakes (at the autoinitialization step). Anyway I still don't quite understand the use of Kalman filter. The given example is good, but I'm still confused how to apply this filter to my data.

Its nice, no doubt.

Simple, pretty, excellent :-))) Thanks a lot!!

VERY GOOD

its great.

Useful Comments in Code.

try to replace inv(A)*B by A\B to speed up, although it's not significant when the matrix size is small

Thank You! Great introduction to the Kalman filter, even if you don't use Matlab.

I need Kalman Filter program.

I get the same error:

kalmanf
??? Input argument "s" is undefined.

Error in ==> kalmanf at 150
if ~isfield(s,'x'); s.x=nan*z; end

Same Error !!!

It will be better if you separate the comment from the m.file and try to add them as "help" in a pdf format.

discrete kalman filter

very good tools
thank you very much

Good demo.
You probably should separete the example, to another m file, named like RunMeDemoKalman.
For the really beginners.

Very easy to use, recommended.

Actually, I am not a beginner at Kalman filter issue. But, i think this is a very useful tool and i wish i got this m-file when i first started to work with Kalman. Because, it is very important for the beginners to have the simplest form of the problem and to see its solution with a simulation program.

this is very good

how con I find calculation of dry gas filter
for natural gas ? please

Be careful. Also we are looking at your downloads records.

This is a very popular file in the File Exchange. The function itself is excelent. However, I just noticed that the example provide with the file is not correct. Somehow, it is misleading to beginers.

In line 131, the process is defined as:
true(end+1) = randn*2 + 12;
i.e. the state is a constant plus a noise. If so, the process in the standard state space form should be:
x(k+1) = 0 * x(k) + 12 + w(k)
i.e. s.A = 0; s.B = 1; s.u = 12;
However, in the file it is wrongly defined as:
s.A = 1; s.B = 0; s.u = 0;
The difference is that the process noise is not dynamically cumulated in the former definition but does in the later.

great

Good for those who want to see what the Kalman Filter is for the first time.
It works and there is a simple example in the m file.

Very Useful Indeed

Nice comments. Awful numerics. Why would you consider multiplying by the inverse? That's horribly inaccurate and slow. Replace

x = inv(H)*z
P = inv(H)*R*inv(H')

with, at least

x = H\z
P = (H\R)/H'

likewise

K = P * H' * inv (lots of stuff)

should be

K = P * H' / (lots of stuff)

further more, if H is not changing, it should be factorized just once and the factors kept (LU or CHOL).

Thanks very much

thanks

very good

Very Helpful, although i would like to see an example with a control vector u.

good

Thank you for your hard work
http://learnbyexamples.org/category/matlab

Thanks very much.

[continued from poste above]

I have solved the problem by modifying the line to;

>> s.x = s.x + K' * (s.z-s.H*s.x); %added transpose of K

This was required as my observance vector (z) was a 2X1 matrix(and so is K and hence they couldn't be multiplied). Although the calculation now works I am still wondering why it doesnt work with the original code.

sehr gut!

thank you for sharing!