Distributed Particle Filters for State Tracking on the Stiefel Manifold Using Tangent Space Statistics

Bordin, Claudio J.; Figueredo, Caio G. de; Bruno, Marcelo G. S.

doi:10.1109/icassp43922.2022.9746305

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“…'s) that are transmitted between nodes over the network. In [23], instead, we built Gaussian parametric approximations on tangent spaces to the Stiefel manifold to represent such p.d.f.'s. A different approach to tangent space parametrization for the Stiefel manifold is also found in [4].…”

Section: Introductionmentioning

confidence: 99%

Diffusion Particle Filtering on the Special Orthogonal Group Using Lie Algebra Statistics

Bordin

Figueredo²,

Bruno

2022

IEEE Signal Process. Lett.

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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.

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Section: Introductionmentioning

confidence: 99%