PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
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, andArjang 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
ACCESS THE FULL ARTICLE
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Fred Daum, Jim Huang, 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