We consider the problem of distributed state estimation of continuous-time stochastic processes using a~network of processing nodes. Each node performs measurement and estimation using the Kalman filtering technique, communicates its results to other nodes in the network, and utilizes similar results from the other nodes in its own computations. We assume that the connection graph of the network is not complete, i.e. not all nodes are directly connected, and that the nodes work asynchronously, i.e. they perform measurement and estimation in time moments independent of each other. We evaluate the impact of the way of propagation of information from most precise nodes over the network on the overall performance of distributed estimation.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-642-39881-0_38
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2014
