Proceedings Paper
Numerical experiments for Gromov’s stochastic particle flow filters| Format | Member Price | Non-Member Price |
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Paper Abstract
We show the results of numerical experiments for a new algorithm for stochastic particle flow filters designed
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: 18 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000J (2 May 2017); doi: 10.1117/12.2248750
Published in SPIE Proceedings Vol. 10200:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI
Ivan Kadar, Editor(s)
PDF: 18 pages
Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000J (2 May 2017); doi: 10.1117/12.2248750
Show Author Affiliations
Jim Huang, 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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