Name
Abstract | ||
|---|---|---|
The interacting multiple model (IMM) estimator outperforms fixed model filters, e.g. the Kalman filter, in scenarios where the targets have periods of disparate behavior. Key to the good performance and low complexity is the mode mixing. Here we propose a systematic approach to mode mixing when the modes have states of different dimensions. The proposed approach is general and encompasses previously suggested solutions. Different mixing approaches are compared, and the proposed methodology is shown to perform very well. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TAES.2015.150015 | IEEE Trans. Aerospace and Electronic Systems |
Keywords | Field | DocType |
Computational modeling,Approximation methods,Acceleration,Multiple model estimator,Gaussian distribution,Kinematics,Estimation | Mathematical optimization,Kinematics,Control theory,Mode (statistics),Algorithm,Kalman filter,Acceleration,Mathematics,Mode mixing,Estimator | Journal |
Volume | Issue | ISSN |
51 | 4 | 0018-9251 |
Citations | PageRank | References |
4 | 0.54 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karl Granström | 1 | 356 | 24.53 |
| PETER WILLETT | 2 | 3421 | 592.93 |
| Yaakov Bar-Shalom | 3 | 460 | 99.56 |