Name
Title | ||
|---|---|---|
Two-stage information filters for single and multiple sensors, and their square-root versions. |
Abstract | ||
|---|---|---|
Accurate states and unknown random bias estimation for well- and ill-conditioned systems are crucial for several applications. In this paper, a fusion of a two-stage Kalman filter and an information filter, and its extensions are considered to estimate the state variables and unknown random bias. Specifically, we propose four extensions of two-stage Kalman filters: two-stage information filter (TSIF), multi-sensor two-stage information filter (M-TSIF) and their square-root versions. The TSIF deals with single-sensor systems whereas the M-TSIF is capable to handle multi-sensor systems. For ill-conditioned systems, numerically stable square-root versions of TSIF and M-TSIF are developed. The performance of the proposed filters (along with the existing two-stage Kalman filter), for well- and ill-conditioned cases, is demonstrated on a quadruple-tank model. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.automatica.2018.09.001 | Automatica |
Keywords | Field | DocType |
Two-stage filters,Information filters,Multi-sensor state estimation | Control theory,Kalman filter,State variable,Square root,Multiple sensors,Mathematics,Information filtering system | Journal |
Volume | Issue | ISSN |
98 | 1 | 0005-1098 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kumar Pakki. Chandra | 1 | 24 | 2.88 |
| Mohamed Darouach | 2 | 261 | 42.82 |