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Partitioning estimation theory is applied in three fundamentally different ways to yield estimators for time delays, feedforward forcing functions, unknown parameters and random forcing functions. Mathematical modeling of human pilots using transient response data taken while hovering a VTOL vehicle is thus possible using a single unifying theory.

The partitioned estimation aloorithms of Lainiotis for the linear discrete time state estimation problems have been generalized in two important ways. First, the inital condition of the estimation problem can be partitioned into the sum of an arbitrary number of jointly Gaussian random variables; and second, these jointly Gaussian random variables may be statistically dependent. The form of the resulting algorithm consists of an imbedded Kalman filter with partial initial conditions and one correction term for each other partition or subdivision of the initial state vector.