On the Identification of Variances and Adaptive Kalman Filtering¶
Mehra, R. (1970). On the Identification of Variances and Adaptive Kalman Filtering. IEEE Transactions on Automatic Control, 15(2), 175-184.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Bayesian Sensor-Fusion Filter
- The discipline that guards against this is to monitor the innovation sequence: for a well-tuned Kalman filter
This sourceUses the innovation sequence to test Kalman-filter optimality: an optimal filter produces white innovations with a model-predicted covariance.
- The discipline that guards against this is to monitor the innovation sequence: for a well-tuned Kalman filter
- Kalman or Particle Filter
- The discipline is to set Q and R from the real noise rather than for a pretty track, and to check that the innovations are actually white.
This sourceIEEE Transactions on Automatic Control. 15(2): 175–184. (1970). Uses observed innovation statistics to identify noise covariances and tests Kalman-filter adequacy through innovation whiteness.
- The discipline is to set Q and R from the real noise rather than for a pretty track, and to check that the innovations are actually white.
Verification¶
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