Anotace:
The paper deals with fusion of state estimates of stochastic dynamic systems. The goal of the contribution is to present main approaches to the estimate fusion which were developed during the last four decades. The hierarchical and decentralised estimation are presented and main special cases are discussed. Namely the following approaches, the distributed Kalman filter, maximum likelihood, channel filters, and the information measure, are introduced. The approaches are illustrated in numerical examples.