NONLINEAR FILTERING OF RANDOM SEQUENCES WITH EXTENDED LEAST-SQUARE METHOD 1
Abstract
For nonlinear random sequences filtering the extended least-square method is proposed. The received suboptimal filter equations include linearization for nonlinear measurement function only. The filter gain coefficient can be calculated by formulas without solving additional equations as in extended Kalman filter. In comparison with the extended Kalman filter, the implementation of the proposed filter has less computational complexity. Examples of a comparative accuracy evaluation of the proposed filter with the extended Kalman filter are given.
About the Authors
V. M. Artemiev
Institute of Applied Physics of the National Academy of Sciences of Belarus, Minsk
Belarus
Corresponding Members of National Academy of Sciences of Belarus, D. Sc. (Engineering), Professor, Chief Researcher
Belarus
Corresponding Members of National Academy of Sciences of Belarus, D. Sc. (Engineering), Professor, Chief Researcher
A. O. Naumov
Institute of Applied Physics of the National Academy of Sciences of Belarus, Minsk
Belarus
Ph. D. (Physics and Mathematics), Head of Laboratory
Belarus
Ph. D. (Physics and Mathematics), Head of Laboratory
L. L. Kokhan
Institute of Applied Physics of the National Academy of Sciences of Belarus, Minsk
Belarus
Ph. D. (Engineering), Senior Researcher
Belarus
Ph. D. (Engineering), Senior Researcher
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Review
For citations:
Artemiev V.M., Naumov A.O., Kokhan L.L. NONLINEAR FILTERING OF RANDOM SEQUENCES WITH EXTENDED LEAST-SQUARE METHOD 1. Informatics. 2018;15(1):60-69. (In Russ.)
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