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.
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 (Presented at SPIE Defense + Security: April 11, 2017; Published: 2 May 2017); https://doi.org/10.1117/12.2248723.
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