Kalman filter
Kalman filter
(OP)
I am working on a tracking algorithm and have heard/read the Kalman filter should give some of the best results.
I have till now seen a lot of (marginally understandable) matrix equations i various book and on the web, but so far I have seen nothing about how to implemment it in 'low-level' code. (Delphi/Pascal, pseudo or ANSI C in order of preference)
Can any in this forum direct me to a good sample here on the web or somewhere else ?
In the first version I will only have a meassure for the position as input, which should simplify things a lot, but even then most of my test have so far either gone 'ballistic' a few samples into my test series or done hardly any filtering.
I have till now seen a lot of (marginally understandable) matrix equations i various book and on the web, but so far I have seen nothing about how to implemment it in 'low-level' code. (Delphi/Pascal, pseudo or ANSI C in order of preference)
Can any in this forum direct me to a good sample here on the web or somewhere else ?
In the first version I will only have a meassure for the position as input, which should simplify things a lot, but even then most of my test have so far either gone 'ballistic' a few samples into my test series or done hardly any filtering.





RE: Kalman filter
there's a teacher of mine that uses Kalmenn's filter's. and teaches them in a master's course. His webpage is:
www.fe.up.pt/~amoreira
and is mail is:
amoreira@fe.up.pt
Best regards, Carlos Cardoso
RE: Kalman filter
http://www.innovatia.com/software/papers...
and something pseudo at:
http://ase.arc.nasa.gov/papers/ASE02/kal...
I now know that my initial concept was wrong.
It seems the gain calculation never see neither the input nor the output of the filter.
It is all somehow done by statistics based uppon an initial estimate of the possible behavior of the tracked object.
RE: Kalman filter
We have been able to track changes upto 20Hz/sec by adjusting the sampling frequency every other sample (2.4 KHz sampling frequency).Fourier based tracking algorithm is fairly easy to implement and of course much easier to understand.
RE: Kalman filter
Tracking and Kalman Filtering Made Easy by Brookner
Kalman filters can be looked upon as an extension of an alpha-beta filter, which uses fixed gain coefficients, which, in turn is a fading memory filter. By adjusting the gain based on the statistics of the data, the filter is able to adapt and optimize to the data in real-time.
One of the best web resource for Kalman filter information is:
http://www.cs.unc.edu/~welch/kalman
TTFN
RE: Kalman filter
Supplemented with the above documents I now have a working filter written in Borland Delphi.
Now comes the task of finding the proper starting parameters.
And of course how to update the parameters without destroying the current track in case the target dynamics change along the way.
RE: Kalman filter
As for the rest, that's more of a track manager question than a filter question. That's highly dependent on your target's expected behavior, e.g., cooperative or not, multiple or not. "Design and Analysis of Modern Tracking Systems" by Blackman and Popoli has some reasonably good stuff, although, not necessarily detailed for someone to build a full-up track manager.
There are also a number of radar tracking books from Artech that might be of use.
TTFN
RE: Kalman filter