altos: Correct model error covariance matrix

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>