Abstract
A minimum variance estimator is derived for linear continuous-time systems with an interrupted observation mechanism which is characterized in terms of the jump Markov process taking on the values of 0 or 1. The approach adopted is that we express the jump Markov process in terms of the initial value and jump times instead of the instantaneous values and then apply Lainiotis' formula regarding the initial value and jump times as unknown system parameters. The resultant optimal algorithm is infinite dimensional, so that feasible approximate estimator algorithms are presented for practical implementation.
