Journal
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
Volume 36, Issue 1, Pages 114-131Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/7.826316
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The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kahman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter's model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed [9]. All of the other filters use internal models that mismodel the true system. T-Ve compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared with simulation results of night control failures that correspond to mismodeled input matrices and output matrices.
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