Bobrovsky-Zakai Bound for Filtering, Prediction and Smoothing of Nonlinear Dynamic Systems

2018-07-13
Fritsche, Carsten
Orguner, Umut
Gustafsson, Fredrik
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.
Citation Formats
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.