Research Article
Three-Axes Mems Calibration Using Kalman Filter and Delaunay Triangulation Algorithm
Table 1
The outline of transformed unscented Kalman filter.
| | (1) Initializing | | Variables pertaining to the state and the square root (sr) of the error covariance matrix | | | Points for Sigma | |
| | (2) Prediction (time update) | | TUKF cubature points after transformation | | | Sample propagation points | | | State prediction | | | SR-error covariance matrix prediction | |
| | (3) Measurement update | | TUKF predicted converted cubature points | | | Sample propagation points | | | Predicting measurement | | | Update of Sr-innovation covariance matrix | | | Update of cross-covariance matrix | | | Updating the Kalman gain | | | Updating the states | | | Update Sr-error covariance matrix | |
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