| Paper ID | SPTM-23.1 | ||
| Paper Title | COOPERATIVE PARAMETER TRACKING ON THE UNIT SPHERE USING DISTRIBUTED ADAPT-THEN-COMBINE PARTICLE FILTERS AND PARALLEL TRANSPORT | ||
| Authors | Caio de Figueredo, Instituto Tecnológico de Aeronáutica, Brazil; Claudio Bordin, Universidade Federal do ABC, Brazil; Marcelo Bruno, Instituto Tecnológico de Aeronáutica, Brazil | ||
| Session | SPTM-23: Bayesian Signal Processing | ||
| Location | Gather.Town | ||
| Session Time: | Friday, 11 June, 14:00 - 14:45 | ||
| Presentation Time: | Friday, 11 June, 14:00 - 14:45 | ||
| Presentation | Poster | ||
| Topic | Signal Processing Theory and Methods: [SSP] Statistical Signal Processing | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | This paper introduces a new distributed Adapt-then-Combine (ATC) diffusion algorithm for cooperative tracking of an unknown state vector that evolves on the unit hypersphere. The adapt step is implemented for a general nonlinear observation model and a dynamic state model defined on the hypersphere using a marginal particle filter (PF). The combine step in turn uses parallel transport to build Gaussian parametric approximations on a common tangent space to the spherical manifold. Performance results are compared to those of competing linear diffusion Extended Kalman Filters and non-cooperative PFs. | ||