Sensitivity of discrete-time Kalman filter to statistical modeling errors
The optimum filtering results of Kalman filtering for linear dynamic systems require an exact knowledge of the process noise covariance matrix Qk, the measurement noise covariance matrix Rk and the initial error covariance matrix P0. In a number of practical solutions, Qk, Rk and P0, are either unkn...
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| Format: | article |
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1999
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| Online Access: | http://hdl.handle.net/10725/3163 http://dx.doi.org/10.1002/(SICI)1099-1514(199909/10)20:5<249::AID-OCA659>3.0.CO;2-2 https://onlinelibrary.wiley.com/doi/abs/10.1002/(SICI)1099-1514(199909/10)20:5%3C249::AID-OCA659%3E3.0.CO;2-2 |
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