Numerical experiments for Gromov’s stochastic particle flow filters

Fred Daum; Arjang Noushin; Jim Huang

doi:10.1117/12.2248750

2 May 2017 Numerical experiments for Gromov’s stochastic particle flow filters

Fred Daum, Arjang Noushin, Jim Huang

Proceedings Volume 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI; 102000J (2017) https://doi.org/10.1117/12.2248750
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

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.

Citation Download Citation

Fred Daum, Arjang Noushin, and 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); https://doi.org/10.1117/12.2248750

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