A Heuristic Reference Recursive Recipe for the Menacing Problem of Adaptively Tuning the Kalman Filter Statistics. Part-2. Real Data Studies (original) (raw)
In the previous paper an adaptive ltering based on a reference recursive recipe was developed and tested on a simulated dynamics of a spring, mass, and damper with a weak nonlinear spring. In this paper the above recipe is applied to a more involved case of three sets of airplane data which have a larger number of state, measurements, and unknown parameters. Further the ight tests cannot always be conducted in an ideal situation of the process noise and the measurement noises being white and Gaussian as is generally assumed in the Kalman lter. The measurements are not available in general with respect to the center of gravity, possess scale and bias factors which will have to be modelled and estimated as well. The coupling between the longitudinal and lateral motion brings in added diculty but makes the problem more interesting. At times the noisy measurements from the longitudinal and lateral motion are input into the longitudinal states. This leads to the resulting equations becom...
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