3 September 1998 Multiple-model estimation with variable structure: likely model set algorithm
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Abstract
A general multiple-model estimator with a variable structure, called likely-model set (LMS) algorithm is presented. It uses a set of models that are not unlikely to match the system mode in effect at the given time. Different versions of the algorithm are discussed. The model set is made adaptive in the simplest version by deleting all unlikely models and activate all models to which a principal model may jump to anticipate the possible system mode transition. The generality, simplicity and ease in the design and implementation of the LMS estimator are illustrated via an example of tracking a maneuvering target and an example of fault detection and identification. Comparison of its cost-effectiveness with other fixed- structure and variable-structure multiple-model estimators is given.
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X. Rong Li, Youmin Zhang, "Multiple-model estimation with variable structure: likely model set algorithm", Proc. SPIE 3373, Signal and Data Processing of Small Targets 1998, (3 September 1998); doi: 10.1117/12.324623; https://doi.org/10.1117/12.324623
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