Name
Title | ||
|---|---|---|
Kalman Filtering With Intermittent Observations: Tail Distribution and Critical Value |
Abstract | ||
|---|---|---|
In this paper, we analyze the performance of Kalman filtering for discrete-time linear Gaussian systems, where packets containing observations are dropped according to a Markov process modeling a Gilbert-Elliot channel. To address the challenges incurred by the loss of packets, we give a new definition of non-degeneracy, which is essentially stronger than the classical definition of observability, but much weaker than one-step observability, which is usually used in the study of Kalman filtering with intermittent observations. We show that the trace of the Kalman estimation error covariance under intermittent observations follows a power decay law. Moreover, we are able to compute the exact decay rate for non-degenerate systems. Finally, we derive the critical value for non-degenerate systems based on the decay rate, improving upon the state of the art. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TAC.2011.2166309 | IEEE Trans. Automat. Contr. |
Keywords | Field | DocType |
Kalman filters,Observability,Estimation error,Mathematical model,Eigenvalues and eigenfunctions,Covariance matrix | Extended Kalman filter,Mathematical optimization,Observability,Markov process,Fast Kalman filter,Control theory,Kalman filter,Gaussian process,Covariance matrix,Mathematics,Covariance | Journal |
Volume | Issue | ISSN |
57 | 3 | 0018-9286 |
Citations | PageRank | References |
44 | 1.52 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yilin Mo | 1 | 891 | 51.51 |
| Bruno Sinopoli | 2 | 2837 | 188.08 |