How to avoid normalization of particle flow for nonlinear filters, Bayesian decisions, and transport

Fred Daum; Jim Huang

doi:10.1117/12.2044122

13 June 2014 How to avoid normalization of particle flow for nonlinear filters, Bayesian decisions, and transport

Fred Daum, Jim Huang

Proceedings Volume 9092, Signal and Data Processing of Small Targets 2014; 90920B (2014) https://doi.org/10.1117/12.2044122
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

We describe four distinct ways to avoid normalization of the probability density for particle flow. We have roughly 20 algorithms to compute particle flow, and the three best algorithms avoid computing the normalization of the conditional probability density of the state. We explain why explicit normalization often spoils the flow. This phenomenon has been noticed by other researchers for completely different applications (e.g., weather prediction), but apparently the benefits of avoiding normalization are not well known.

Citation Download Citation

Fred Daum and Jim Huang "How to avoid normalization of particle flow for nonlinear filters, Bayesian decisions, and transport", Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920B (13 June 2014); https://doi.org/10.1117/12.2044122

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