2 May 2017 Numerical experiments for Gromov’s stochastic particle flow filters
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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.
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Fred Daum, Arjang Noushin, Jim Huang, "Numerical experiments for Gromov’s stochastic particle flow filters", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102000J (2 May 2017); doi: 10.1117/12.2248750; https://doi.org/10.1117/12.2248750
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