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Proceedings Paper

Fourier transform particle flow for nonlinear filters
Author(s): Fred Daum; Jim Huang
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Paper Abstract

We derive five new algorithms to design particle flow for nonlinear filters using the Fourier transform of the PDE that determines the flow of particles corresponding to Bayes’ rule. This exploits the fact that our PDE is linear with constant coefficients. We also use variance reduction and explicit stabilization to enhance robustness of the filter. Our new filter works for arbitrary smooth nowhere vanishing probability densities.

Paper Details

Date Published: 23 May 2013
PDF: 9 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450R (23 May 2013); doi: 10.1117/12.2001666
Show Author Affiliations
Fred Daum, Raytheon Co. (United States)
Jim Huang, Raytheon Co. (United States)


Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

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