书目名称 | State Estimation for Nonlinear Continuous–Discrete Stochastic Systems |
副标题 | Numerical Aspects an |
编辑 | Gennady Yu. Kulikov,Maria V. Kulikova |
视频video | |
概述 | Resolves problem of strong nonlinearities and sparse measurement and introduces the notion of accurate state estimation.Shows the reader how to treat stiff, ill-conditioned continuous-time stochastic |
丛书名称 | Studies in Systems, Decision and Control |
图书封面 |  |
描述 | .This book addresses the problem of accurate state estimation in nonlinear continuous-time stochastic models with additive noise and discrete measurements. Its main focus is on numerical aspects of computation of the expectation and covariance in Kalman-like filters rather than on statistical properties determining a model of the system state. Nevertheless, it provides the sound theoretical background and covers all contemporary state estimation techniques beginning at the celebrated Kalman filter, including its versions extended to nonlinear stochastic models, and till the most advanced universal Gaussian filters with deterministically sampled mean and covariance. In particular, the authors demonstrate that, when applying such filtering procedures to stochastic models with strong nonlinearities, the use of adaptive ordinary differential equation solvers with automatic local and global error control facilities allows the discretization error—and consequently the state estimation error—to be reduced considerably. For achieving that, the variable-stepsize methods with automatic error regulation and stepsize selection mechanisms are applied to treating moment differential equations ar |
出版日期 | Book 2024 |
关键词 | Continous–Discrete Stochastic Systems; State-estimation Problems; Extended Kalman Filter; Cubature Kalm |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-61371-5 |
isbn_softcover | 978-3-031-61373-9 |
isbn_ebook | 978-3-031-61371-5Series ISSN 2198-4182 Series E-ISSN 2198-4190 |
issn_series | 2198-4182 |
copyright | Springer Nature Switzerland AG 2024 |