We consider a time varying sensor network comprised of a group of agents equipped with communication capabilities, and we address applications where communication between agents is highly bandwidth limited as for instance in underwater missions. We use the Bayesian formalism to derive data fusion equations in which each sensor maintains an individual estimate of the state of a dynamical process. Data sharing between agents is defined by a time-varying network topology. We show that error covariances associated to estimates obtained with the independent opinion pool fusion scheme asymptotically agree if the communication network is partially asynchronous.
- Dynamic Systems and Control Division
Cooperative Kalman Filtering With Data Fusion in Time Varying Communication Networks
- Views Icon Views
- Share Icon Share
- Search Site
Spinello, D, & Stilwell, DJ. "Cooperative Kalman Filtering With Data Fusion in Time Varying Communication Networks." Proceedings of the ASME 2010 Dynamic Systems and Control Conference. ASME 2010 Dynamic Systems and Control Conference, Volume 1. Cambridge, Massachusetts, USA. September 12–15, 2010. pp. 947-954. ASME. https://doi.org/10.1115/DSCC2010-4192
Download citation file: