Overview of nonlinear Bayesian filtering algorithm

Procedia Engineering(2011)

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摘要
For many nonlinear dynamic systems, the choice of nonlinear Bayesian filtering algorithms is important. In this paper, we review the application of both optimal and suboptimal Bayesian algorithms for state estimation, and the latter is divided into four types, that is function approximation, numerical approximation, Gaussian sum approximation and sampling approximation. Then four typical suboptimal Bayesian algorithms are mainly discussed, that is EKF, STF, UKF and PF. Finally, characters of nonlinear Bayesian filtering algorithms are summarized, and further development is forecasted.
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关键词
Nonlinear system,Bayesian filtering,Particle filter,Unscented Kalman filter,trong tracking filter
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