Discrete linear recursive smoothing for systems with uncertain observations
Robert A. Monzingo · IEEE Transactions on Automatic Control · 1981
The least-squares smoothing estimate for discrete linear systems with uncertain observations is investigated. The observations may contain noise alone, and the uncertainty in the observations is governed by a binary switching sequence\gammak, where\gammakmay be regarded as a mixture process and is specified by a conditional probability distribution. Examples of such systems are found in multichannel data links with random interruptions, and such mixture sequences can also serve as models for a communication channel with multiplicative noise.