| 摘要 |
The present invention provides a data fusion architecture with a plurality of sensors, optionally position measuring equipment (PMEs). Each sensor supplies measurement data x1, x2....x M and is associated with accuracy data H1, H2...H M indicative of the accuracy of the supplied measurement data. Sub-processing units derives first estimates sf1, sf2...sf M and second estimates Hn1, Hn2...Hn M of the variability of the measurement data supplied by the respective sensor. The first estimates are derived by processing the measurement data x1, x2....x M and the second estimates are derived by processing the accuracy data H1, H2...H M. The first and second estimates are combined in a multiplier to derive overall estimates .sigma.1, .sigma.2....sigma. M of the variability of the measurement data supplied by the respective sensor. Data fusion means such as a Kalman filter combines the measurement data supplied by each sensor and the overall estimates .sigma.1, .sigma.2....sigma. M for each sensor. |
