| 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 |
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| Virtual Presentation |
Click here to watch in the Virtual Conference |
| 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. |
