Abstract
Deterministic sampling filters, including Unscented Kalman filter(UKF), central difference Kalman filter(CDKF) and cubature Kalman filter(CKF), are a class of nonlinear suboptimal Gaussian filtering algorithms based on deterministic and analytical sampling approximation, which have advantages of high precision and simple implementation, and have been received wide attention from scholars. The basic principle of deterministic sampling filter is described, and its research situation is summarized in detail, including various improved methods and applications in different areas. Then the problems of deterministic sampling filter at present are analyzed and presented. Finally, its development tendency and research orientation are prospected.
| Original language | English |
|---|---|
| Pages (from-to) | 801-812 |
| Number of pages | 12 |
| Journal | Kongzhi yu Juece/Control and Decision |
| Volume | 27 |
| Issue number | 6 |
| State | Published - Jun 2012 |
Keywords
- Deterministic sampling filter
- Nonlinearity
- Optimal framework
- Polynomial interpolation
- Spherical-radial rule
- Unscented transformation