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Bobrovsky-Zakai Bound for Filtering, Prediction and Smoothing of Nonlinear Dynamic Systems
Date
2018-07-13
Author
Fritsche, Carsten
Orguner, Umut
Gustafsson, Fredrik
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this paper, recursive Bobrovsky-Zakai bounds for filtering, prediction and smoothing of nonlinear dynamic systems are presented. The similarities and differences to an existing Bobrovsky-Zakai bound in the literature for the filtering case are highlighted. The tightness of the derived bounds are illustrated on a simple example where a linear system with non-Gaussian measurement likelihood is considered. The proposed bounds are also compared with the performance of some well-known filters/predictors/smoothers and other Bayesian bounds.
Subject Keywords
Bobrovsky-Zakai bound
,
State estimation
,
Nonlinear
,
Filtering
,
Smoothing
,
Prediction
URI
https://hdl.handle.net/11511/38070
DOI
https://doi.org/10.23919/icif.2018.8455541
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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BibTeX
C. Fritsche, U. Orguner, and F. Gustafsson, “Bobrovsky-Zakai Bound for Filtering, Prediction and Smoothing of Nonlinear Dynamic Systems,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38070.