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- W560310351 abstract "Problem of vehicle state estimation in case when measurement disturbances fail to be Gaussian because of coarse measurement errors /outliers/ occurrence, is considered in the paper. Dynamical model of the vehicle is assumed in form of discrete, linearized, multivariable equations of motion. Supposing nearly-Gaussian class of measurement disturbances distributions, several multivariable robust estimation algorithms are developed and compared. Comparative analysis of the algorithms is done by means of Monte-Carlo simulations. Some results of simulations of two dimensional model of the NASA F8 fly-by-wire aircraft are presented and the effectiveness of various state estimation algorithms, calculated from 1000 Monte-Carlo runs is compared. The analysis shows high effectiveness of the robust algorithms which clearly outperform normal Kaiman filters." @default.
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- W560310351 date "1982-06-01" @default.
- W560310351 modified "2023-10-16" @default.
- W560310351 title "Comparative Study of Robust Methods of Vehicle State Estimation" @default.
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- W560310351 doi "https://doi.org/10.1016/s1474-6670(17)63096-9" @default.
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