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John D

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Comments and Ratings by John D		View all 1 - 3 of 3
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09 Jun 2010	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	[continued from poste above] As expected my matrices were wrong! Thanks for the example!
09 Jun 2010	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	[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.
08 Jun 2010	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	I get an error during the correction step. >> s.x = s.x + K(s.z-s.Hs.x); Error using==>mtimes Inner matrix dimensions must agree The error makes sense given the size of my matrices but I don't see how they could be wrong. Is this code expected to not work for a system with two observer inputs (position and speed)? Thanks for the help! ps: let me know if you need more info - tried to keep it short.

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basic kalman filter, discrete filter, files

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27 Jan 2010		41 Complete GUI Examples 41 working GUIs to read and learn. Author: Matt Fig	example, gui, examples, files, guide, how to	774	67	4.97101 5.0 \| 72 ratings
12 Oct 2005		Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	basic kalman filter, kalman filter, discrete filter, linear, imtransform, filter analysis	414	98	4.44944 4.4 \| 91 ratings

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12 Oct 2005		Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering. Author: Michael Kleder	basic kalman filter, kalman filter, discrete filter, linear, imtransform, filter analysis	414	98	4.44944 4.4 \| 91 ratings

Comments and Ratings Matching John D's Watch List			1-5 of 134
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10 Apr 2013	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	jakub	In other words, how to draw their values, provided they are stored in my data.mat? Will the "plot" are the same and I have to use a loop "for"? Ask directly about the code sample, it's here I deal with a couple of hours.	Comment only
09 Apr 2013	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	jakub	My case: >> clear s >> s.x = 12; >> s.A = 1; >> s.Q = 2^2; >> s.H = 1; >> s.R = 2^2; >> s.B = 0; >> s.u = 0; >> s.x = nan; >> s.P = nan; >> s.z = [1 2 3 4 5 6 7 8 9 22 3 4 5 6 7 8 88]; >> kalmanf(s); >> figure >> hold on >> grid on >> hz=plot(s.z,'r.') >> hk=plot(s,'b-') Error using plot Conversion to double from struct is not possible. Where is the problem ? Thank u	Comment only
13 Feb 2013	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	zhang blue		5
07 Feb 2013	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	Tim		5
07 Feb 2013	Learning the Kalman Filter Basic Kalman filter, heavily commented, for beginners to Kalman filtering.	Tim	I am new to k. filtering, and I don't understand the following: the covariance matrix P appears to be only a function of the following inputs: A (defined by the system), P (itself), Q (known p.noise cov.), and H (typically identity), and also the Kalman gain K. K itself is a function only of P, H, and R (known m.noise cov.). None of these are re-defined during iteration except P. How then is the estimate of the covariance matrix P tied to observations z? The result of this appears to be that the Kalman gain explodes by the third or fourth iteration, making the output mirror the noisy input. This seems to be what Enver Bahar is noticing too, I think.	3