Filtering of high dynamics trajectory data using spline function models

Cubic spline functions are used to characterize the powered portion of high performance solid fuel rocket trajectories, and the use of such a model for Kalman filtering is considered. The filter is evaluated on the basis of maximum and rms error; and the effects of model errors, measurement errors, noise level, and timing errors are considered for various sample rates. Instrument dynamics are included in the system model. Simulation results indicate the performance to be superior to that of several other filters in use.