State estimation under uncertain observations with unknown statistics

Abstract

The asymptotic behavior of a Bayes optimal adaptive estimation scheme for a linear, discrete-time system with interrupted observations is investigated. The interrupted observation mechanism is expressed in terms of a stationary two-state Markov chain. The transition probability matrix is unknown and can take values only from a finite set.