16 September 2011 Numerical experiments for Coulomb's law particle flow for nonlinear filters
Author Affiliations +
Abstract
We show numerical results for a new nonlinear filtering algorithm that is analogous to Coulomb's law. We have invented a new theory of exact particle flow for nonlinear filters. The flow of particles corresponding to Bayes' rule is computed from the gradient of the solution of Poisson's equation, and it is analogous to Coulomb's law. Our theory is a radical departure from other particle filters in several ways: (1) we compute Bayes' rule using a flow of particles rather than as a pointwise multiplication; (2) we never resample particles; (3) we do not use a proposal density; (4) we do not use importance sampling or any other MCMC algorithm; and (5) our filter is roughly 6 to 8 orders of magnitude faster than standard particle filters for the same accuracy.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fred Daum, Jim Huang, Arjang Noushin, "Numerical experiments for Coulomb's law particle flow for nonlinear filters", Proc. SPIE 8137, Signal and Data Processing of Small Targets 2011, 81370E (16 September 2011); doi: 10.1117/12.887521; https://doi.org/10.1117/12.887521
PROCEEDINGS
15 PAGES


SHARE
RELATED CONTENT

Particle flow for nonlinear filters with log-homotopy
Proceedings of SPIE (April 16 2008)
Nonlinear filters with particle flow
Proceedings of SPIE (September 04 2009)
Generalized particle flow for nonlinear filters
Proceedings of SPIE (April 15 2010)
Nonlinear filters with log-homotopy
Proceedings of SPIE (September 25 2007)

Back to Top