A practical note on evaluating Kalman filter performance optimality and degradation

摘要: This paper presents useful remarks to the readers on Kalman filter (KF) performance optimality, degradation, and some innovation related parameters. Guidelines for efficient approach evaluation of KF optimality sensitivity analysis are presented. Performance degradation due uncertainty in process measurement noise statistics is discussed. Consistency check between filter-calculated covariances versus actual mean square errors provided, which can be used not only as a verification procedure filtering correctness, but also making trade-off designing suitable filter. In addition numerical algorithms, Matlab programs accompanied where necessary getting better insight practical implementation. Exploration behaviour based parameters adaptive system integrity designs, including covariance sequence, degree mismatch (DOM), divergence (DOD), etc., involved.