A New Generalized Residual Multiple Model Adaptive Estimator of Parameters and States
Document Type
Article
Publication Date
5-2006
Abstract
This article develops a modification to the standard Multiple Model Adaptive Estimator (MMAE) which allows the use of a new “generalized residual” in the hypothesis conditional probability calculation. The generalized residual is a linear combination of the traditional Kalman filter residual and the “post-fit” Kalman filter residual which is calculated after measurement incorporation. This new modified MMAE is termed a Generalized Residual Multiple Model Adaptive Estimator (GRMMAE). A derivation is provided for the hypothesis conditional probability formula which the GRMMAE uses to calculate probabilities that each elemental filter contains the correct parameter value.
Abstract excerpt © Elsevier
DOI
10.1016/j.mcm.2005.12.003
Source Publication
Mathematical and Computer Modelling
Recommended Citation
Ormsby, C. D., Raquet, J. F., & Maybeck, P. S. (2006). A new generalized residual multiple model adaptive estimator of parameters and states. Mathematical and Computer Modelling, 43(9–10), 1092–1113. https://doi.org/10.1016/j.mcm.2005.12.003
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