HYBRID ESTIMATION ALGORITHMS .2.

The equations of state evolution of a hybrid system are nonlinear and generate non-Gaussian sample paths. For this reason, the optimal, mean -square estimate of the state is difficult to determine. in an earlier paper (Ref. 1), a useful approximation to the optimal estimator was d erived for the case where there is a direct, albeit noisy, measurement of the modal state. Although this algorithm has proven serviceable, i t is restricted to applications in which the base-state path is contin uous. in this paper, the result is extended to the case in which there are base-state discontinuities of a particular sort. The algorithm is tested on a target tracking problem and is shown to be superior to bo th the extended Kalman filter and the estimator derived in Ref. 1.