Paper
27 April 2010 A fresh perspective on research for nonlinear filters
Fred Daum, Jim Huang
Author Affiliations +
Abstract
We give a fresh perspective on research for nonlinear filters with particle flow. Such research is an interesting mixture of theory and numerical experiments, as well as tradeoffs in filter implementation using GPUs and fast approximate k-NN algorithms, and fast approximate Poisson solvers. Our fundamental idea is to compute Bayes' rule using an ordinary differential equation (ODE) rather than a pointwise multiplication; this solves the problem of particle degeneracy. Our filter is many orders of magnitude faster than standard particle filters for high dimensional problems, and it is several orders of magnitude more accurate than the EKF for difficult nonlinear problems, including problems with multimodal densities.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fred Daum and Jim Huang "A fresh perspective on research for nonlinear filters", Proc. SPIE 7697, Signal Processing, Sensor Fusion, and Target Recognition XIX, 769705 (27 April 2010); https://doi.org/10.1117/12.846741
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Cited by 9 scholarly publications.
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KEYWORDS
Particles

Particle filters

Nonlinear filtering

Filtering (signal processing)

Monte Carlo methods

Electronic filtering

Fluid dynamics

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