Name
Title | ||
|---|---|---|
A bound approach to asymptotic optimality in non-linear filtering of diffusion processes |
Abstract | ||
|---|---|---|
The asymptotic behavior as a small parameter ε→0 is investigated for one-dimensional non-linear filtering problems. Both weakly non-linear systems (WNL) and systems measured through a low noise channel are considered. Upper and lower bounds on the optimal mean square error combined with perturbation methods are used to show that, in the case of WNL, the Kalman filter formally designed for the underlying linear systems is asymptotically optimal in some sense. In the case of systems with low measurement noise, three asymptotically optimal filters are provided, one of which is linear. Examples with simulation results are provided. |
Year | DOI | Venue |
|---|---|---|
1989 | 10.1016/0005-1098(89)90028-9 | Automatica |
Keywords | Field | DocType |
Non-linear filtering,Kalman filtering,estimation error bounds,optimal filtering,perturbation techniques,stochastic systems,state estimation | Mathematical optimization,Nonlinear system,Linear system,Upper and lower bounds,Mean squared error,Filter (signal processing),Kalman filter,Asymptotic analysis,Asymptotically optimal algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
25 | 5 | 0005-1098 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lahcen Saydy | 1 | 66 | 17.99 |
| G. L. Blankenship | 2 | 22 | 3.25 |