Scalable Distributed Kalman Filtering for Mass-Spring Systems
This paper considers Kalman Filtering for massspring systems. The aim is a scalable distributed implementation where nodes communicate in a sparse pattern and the state estimate for each node is available locally and usable for control. The focus is on translation invariant systems, to make use of the powerful results available based on Fourier Transform methods. In this case it is known that Kalm
