论文信息 - A BIAS Identification and State Estimation Methodology for Nonlinear Systems

A BIAS Identification and State Estimation Methodology for Nonlinear Systems

Abstract A computational algorithm for the identification of input and output biases in discrete-time nonlinear stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach is illustrated by identifying instrument biases using a terminal configured vehicle simulation.

A. K. Caglayan | R. Lancraft

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