Navigation system applications of sigma-point Kalman filters for nonlinear estimation and sensor fusion
US7289906B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 4, 2005 |
| Grant date | Oct 30, 2007 |
| Priority date | — |
| Expiry date | Sep 19, 2025 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01C21/165
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method of estimating the navigational state of a system entails acquiring observation data produced by noisy measurement sensors and providing a probabilistic inference system to combine the observation data with prediction values of the system state space model to estimate the navigational state of the system. The probabilistic inference system is implemented to include a realization of a Gaussian approximate random variable propagation technique performing deterministic sampling without analytic derivative calculations. This technique achieves for the navigational state of the system an estimation accuracy that is greater than that achievable with an extended Kalman filter-based probabilistic inference system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.