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Proceedings Paper

Generalized Gromov method for stochastic particle flow filters
Author(s): Fred Daum; Jim Huang; Arjang Noushin
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Paper Abstract

We describe a new algorithm for stochastic particle flow filters using Gromov’s method. We derive a simple exact formula for Q in certain special cases. The purpose of using stochastic particle flow is two fold: improve estimation accuracy of the state vector and improve the accuracy of uncertainty quantification. Q is the covariance matrix of the diffusion for particle flow corresponding to Bayes’ rule.

Paper Details

Date Published: 2 May 2017
PDF: 13 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000I (2 May 2017); doi: 10.1117/12.2248723
Show Author Affiliations
Fred Daum, Raytheon Co. (United States)
Jim Huang, Raytheon Co. (United States)
Arjang Noushin, Raytheon Co. (United States)


Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)

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