Efficiency analysis of a filtering algorithm for discrete-time linear stochastic systems with polynomial measurements

A filtering algorithm is presented for discrete-time linear stochastic systems with polynomial measurements. The techniques to evaluate its efficiency are proposed. The algorithm performance is demonstrated by solving two navigation data processing problems, map-aided navigation using geophysical fi...

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Bibliographic Details
Published in:Journal of the Franklin Institute 2019-07, Vol.356 (10), p.5573-5591
Main Authors: Stepanov, O.A., Vasiliev, V.A., Toropov, A.B., Loparev, A.V., Basin, М.V.
Format: Article
Language:English
Subjects:
Algorithms
Autonomous navigation
Autonomous underwater vehicles
Computer simulation
Data processing
Discrete element method
Discrete time systems
Extended Kalman filter
Geophysics
Kalman filters
Measurement
Polynomials
Stochastic models
Stochastic systems
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Summary:A filtering algorithm is presented for discrete-time linear stochastic systems with polynomial measurements. The techniques to evaluate its efficiency are proposed. The algorithm performance is demonstrated by solving two navigation data processing problems, map-aided navigation using geophysical fields and single-beacon navigation for an autonomous underwater vehicle. The designed polynomial filter is compared to the extended Kalman filter, which is commonly used in practice. The simulation results reveal advantages of the polynomial algorithm. The obtained conclusions are reported.
ISSN:0016-0032
1879-2693
0016-0032
DOI:10.1016/j.jfranklin.2019.02.036