Numerical experiments for Gromov’s stochastic particle flow filters

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.