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Diffusion Particle Filtering on the Special Orthogonal Group using Lie Algebra Statistics
  • Claudio Bordin ,
  • Caio Gomes de Figueredo ,
  • Marcelo Bruno
Claudio Bordin
Universidade Federal do ABC

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Caio Gomes de Figueredo
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Marcelo Bruno
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Abstract

In this paper, we introduce new distributed diffusion algorithms to track a sequence of hidden random matrices that evolve on the special orthogonal group. The algorithms are based on the Adapt-then-Combine and the Random Exchange methods, and diffuse Gaussian approximations of posterior densities computed in the Lie algebra of the special orthogonal group. Simulation results show that, in a scenario with strongly nonlinear observation functions, the proposed algorithms perform similarly to the centralized particle filter estimator and can outperform competing Extended Kalman Filters.
2022Published in IEEE Signal Processing Letters volume 29 on pages 2058-2062. 10.1109/LSP.2022.3210870