A plethora of open problems in particle flow research for nonlinear filters, Bayesian decisions, Bayesian learning, and transport

Fred Daum; Jim Huang

doi:10.1117/12.2217755

17 May 2016 A plethora of open problems in particle flow research for nonlinear filters, Bayesian decisions, Bayesian learning, and transport

Fred Daum, Jim Huang

Author Affiliations +

Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 98420I (2016) https://doi.org/10.1117/12.2217755
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

We describe many open problems for research in particle flows to compute Bayes’ rule for nonlinear filters, Bayesian decisions and Bayesian learning as well as transport. Particle flow mitigates particle degeneracy, which is the main cause of the curse of dimensionality for particle filters. Particle flow filters are many orders of magnitude faster to compute in real time compared with standard particle filters for the same accuracy for difficult high dimensional problems.

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Fred Daum and Jim Huang "A plethora of open problems in particle flow research for nonlinear filters, Bayesian decisions, Bayesian learning, and transport", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420I (17 May 2016); https://doi.org/10.1117/12.2217755

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