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authorKeith Packard <keithp@keithp.com>2013-01-16 15:01:12 -0800
committerKeith Packard <keithp@keithp.com>2013-01-16 15:21:24 -0800
commitdd60d85d07b881ac03294a8cf607e469f2e69610 (patch)
tree255e3d9b4fc65b10c140551d685f84ec6461a138 /src/kalman/load_csv.5c
parent994ff76a064dcbd3113db771cd9cd9591fd68dea (diff)
altos: Correct model error covariance matrix
Finally found a couple of decent references on how to set the model (process) error covariance matrix. The current process matrix turns out to be correct for a continuous kalman filter (which isn't realizable, of course). For a discrete filter, the error in modeled acceleration (we model it as a constant) needs to be propogated to the speed and position portions of the matrix. The correct matrix is seen in this paper: On Reduced-Order Kalman Filters For GPS Position Filtering J. Shima 6/2/2001 This references an older paper which is supposed to describe the derivation of the matrix: Singer, R.A., “Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets,” IEEE Transactions of Aerospace and Electronic Systems, AES-5, July 1970, pp. 473-483. This change has a minor effect on the computed correction coefficients; it should respond more reasonably to acceleration changes now. Signed-off-by: Keith Packard <keithp@keithp.com>
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