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2 May 2017 Generalized Gromov method for stochastic particle flow filters
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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.
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Fred Daum, Jim Huang, and Arjang Noushin "Generalized Gromov method for stochastic particle flow filters", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000I (2 May 2017); https://doi.org/10.1117/12.2248723
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