23 May 2013 Fourier transform particle flow for nonlinear filters
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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.
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Fred Daum, Fred Daum, Jim Huang, Jim Huang, "Fourier transform particle flow for nonlinear filters", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450R (23 May 2013); doi: 10.1117/12.2001666; https://doi.org/10.1117/12.2001666

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